MCP Server
OWOX Data Marts exposes a Model Context Protocol (MCP) server. It lets AI assistants and MCP-compatible clients connect to your project data using standard OAuth authorization.
Use the MCP server to explore your data marts in plain language with an AI assistant like Claude or ChatGPT. You never have to leave the assistant. The assistant can summarize the available catalog and inspect data mart fields. It can run bounded queries, list destinations and reports, and set up report delivery. It can also manage report schedules and start report runs for supported push destinations. See Available tools for exactly what it can and cannot do.
Prerequisites
Section titled “Prerequisites”- An active OWOX Data Marts project with at least one published data mart. New to Data Marts? See how to create a connector-based or SQL-based Data Mart. You can connect before creating one — the assistant then explains what a data mart is and where to create it (see The assistant says there are no data marts).
- One of the supported clients: Claude Desktop or Claude web (claude.ai) — the recommended way to connect — or ChatGPT. Any other client that supports the MCP Streamable HTTP transport with OAuth 2.0 will also work.
- A client plan that allows MCP connectors. Adding an MCP server like OWOX may require a paid plan in Claude or ChatGPT. Check your client’s current plan requirements.
Step 1: Connect your AI assistant
Section titled “Step 1: Connect your AI assistant”Set up whichever assistant you use — you only need one. We recommend Claude Desktop or Claude web as the default client. Connect to the shared MCP server, https://mcp.owox.com/mcp: the client discovers its OAuth endpoints and registers itself automatically, so there is no client ID, secret, or token to copy. You select your project during authorization — see Step 2.
Note: Connecting to multiple projects, or scripting the setup from a URL your OWOX UI or API already gave you? See Use a project-specific URL below.
Claude Desktop (recommended)
Section titled “Claude Desktop (recommended)”-
Open Claude and go to Settings → Connectors.
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Click Add → Browse connectors.
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Find OWOX Data Marts and click Connect.
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Claude opens a browser window to complete authorization. Follow the steps in Step 2.
To confirm your MCP server is configured correctly, open the Connectors section and check that OWOX Data Marts is enabled.
Claude web (claude.ai)
Section titled “Claude web (claude.ai)”- Open claude.ai and go to Settings → Connectors.
- Click Add → Browse connectors.
- Find OWOX Data Marts and click Connect.
- Claude opens an authorization flow in the same browser. Follow the steps in Step 2.
ChatGPT
Section titled “ChatGPT”- Open ChatGPT and go to Plugins.
- Find OWOX Data Marts in the list of plugins and click Install plugin.
- Click Sign in with OWOX Data Marts. ChatGPT opens an authorization window. Follow the steps in Step 2.
- You will see OWOX Data Marts is installed, indicating the integration is connected.
- Click Try in chat.
- In a new chat, select or enable the OWOX plugin if ChatGPT does not use it automatically.
Use a project-specific URL
Section titled “Use a project-specific URL”The steps above connect the shared MCP server and let you pick a project during authorization. If OWOX UI or API already gave you a project’s URL — https://{projectId}.mcp.owox.com/mcp — you can connect that instead: add it as a custom connector rather than picking OWOX Data Marts from the client’s connector directory (in Claude, use Add → Add custom connector). The projectId is already in MD5 format; it is only a stable URL identifier and does not grant access by itself.
A project-specific URL uses the same OAuth flow and the same MCP tools as the shared one, but it skips the project selection screen in Step 2 — authorization still succeeds only if the signed-in user is an active member of that project.
If you connect project-specific MCP servers for multiple projects, give each connection a unique name, such as Marketing or Finance. This makes it easier to select the right server and tell your assistant which project’s MCP tools to use.
Step 2: Authorize access
Section titled “Step 2: Authorize access”When the MCP client first connects, it opens a browser window to complete OAuth 2.0 authorization. You only complete two interactive steps:
- Sign in to your OWOX account if you do not already have an active session.
- Select a project — for
https://mcp.owox.com/mcp, if you belong to more than one project, a selection screen appears. Choose the project you want this MCP connection to use and click Next. If you usehttps://{projectId}.mcp.owox.com/mcp, this screen is skipped because the project is already part of the server URL.
There is no separate permissions-consent screen. Once you sign in and select a project, the client receives an access token. It uses that token automatically for all subsequent requests. The token is bound to the project you selected and to the requested scope.
Access tokens are short-lived, and the client refreshes them automatically in the background — you stay connected without signing in again. You only need to reconnect manually if the refresh fails — for example, after your OWOX session is revoked. You also reconnect manually when you want to switch projects.
Add project context for your assistant
Section titled “Add project context for your assistant”Project admins can provide up to 10,000 characters of business context, terminology, and project-specific conventions for AI assistants in Project settings → Overview → Description. OWOX returns the complete description through get_project_context; the MCP instructions tell the assistant to call that tool before its first project-specific operation.
Do not put passwords, API keys, or other secrets in the description. All project members can see it, and connected MCP clients may send it to their AI provider. After changing the description, the updated value is available on the next get_project_context call; reconnecting the MCP client is not required.
Step 3: Verify the connection
Section titled “Step 3: Verify the connection”Confirm everything works before relying on it. In your assistant, send:
Which OWOX project am I connected to?
The assistant calls the get_project_context tool and replies with your project title, your role, and the project status. If you see your project name, the connection is working. If instead you get an authorization or “no tools available” error, see Troubleshooting.
Switch projects or disconnect
Section titled “Switch projects or disconnect”Project selection is fixed when you authorize. Switching projects means reconnecting with the shared server and selecting another project, or reconnecting with a different project-specific server URL. Where you manage the connection depends on the client:
- Claude Desktop / Claude web: Settings → Connectors, then open the OWOX connector to disconnect or reconnect it.
- ChatGPT: Settings → Apps, then open the OWOX app to disconnect or reconnect it.
To switch projects, disconnect, then reconnect and sign in again. If you use the shared server, choose the project during authorization. If you use a project-specific server, use the URL for the target project.
Available tools
Section titled “Available tools”Once connected, the MCP server exposes twenty tools across two scopes:
mcp:read: discovery and status tools —summarize_data_catalog,get_project_context,list_data_marts,get_relevant_data_marts_by_prompt,get_data_mart_details_by_id,list_destinations,get_data_mart_reports,get_relevant_reports_by_prompt,get_report_output_schema,list_report_run_schedules,get_report_run_status.mcp:write: tools that create, change, run, or bill something —query_data_mart,add_destination,add_report,update_report,delete_report,create_report_run_schedule,update_report_run_schedule,delete_report_run_schedule,run_report.query_data_martand the report-run schedule mutation tools also requiremcp:read.query_data_martreads data rows, records each call in Run History, and costs credits per call. Your MCP client may ask you to confirm before it calls one of these.
summarize_data_catalog
Section titled “summarize_data_catalog”Returns a high-level summary of the published data mart catalog available to this MCP connection. It helps the assistant answer broad orientation questions like “What data is available here?” or “Where should I start?” without querying actual data rows.
Returns:
| Field | Description |
|---|---|
project_id | Project identifier |
data_mart_count | Number of published data marts visible to you |
top_data_marts_by_connectivity | Data marts ranked by configured relationship connectivity |
getting_started | Only when the catalog is empty: links and next steps for creating the first data mart (see The assistant says there are no data marts) |
_instruction | Internal guidance for the assistant on how to summarize the returned catalog |
Each top_data_marts_by_connectivity item includes id, title, description, url, relationship_count, reports_count, triggers_count, and updated_at.
Use this tool when the user asks what can be analyzed in the project. It does not return sample values, data freshness, row counts, or any actual data rows.
get_project_context
Section titled “get_project_context”Returns information about the OWOX project that this MCP connection is authorized for, including the complete admin-maintained project description when one is configured.
Returns:
| Field | Description |
|---|---|
current_project.id | Project identifier |
current_project.title | Project display name |
current_project.description | Complete project description, or null when none is configured |
current_project.status | Project status |
current_project.roles | Your roles in this project |
current_project.created_at | Project creation date |
project_switching | Instructions for switching to a different project |
The assistant should use this tool before its first project-specific operation so it has the project’s business context. You can also use it to confirm which project is active or selected. Call it again after an admin changes the project description to get the latest value.
list_data_marts
Section titled “list_data_marts”Lists data marts visible to you in the current project. By default, it returns published data marts. You can explicitly request draft data mart metadata, but drafts cannot be inspected or queried through other MCP data mart tools.
Input:
| Field | Description |
|---|---|
status | Optional: published (default) returns queryable data marts; draft returns draft metadata for catalog browsing only. |
Returns an array of data mart objects:
| Field | Description |
|---|---|
id | Data mart identifier |
title | Data mart name |
description | Data mart description |
url | Link to open the data mart in OWOX Data Marts |
status | Current status: PUBLISHED or DRAFT. Response values are uppercase and differ from the lowercase input filter values. |
updated_at | Last update timestamp |
Use this tool to discover available data marts before running queries or building reports.
The response also includes project.id and project.title, so the assistant can state which project its discovery results belong to.
When you see no published data mart, the response also includes getting_started — links and next steps for creating the first one (see The assistant says there are no data marts).
The list reflects your access: it includes only the data marts your project role permits you to see. If a data mart you expect is missing, check your role in that project.
get_relevant_data_marts_by_prompt
Section titled “get_relevant_data_marts_by_prompt”Finds the data marts most relevant to a natural-language question, ranked by relevance. Use it to discover which data marts can answer a specific question without listing the whole project.
Input:
| Field | Description |
|---|---|
prompt | Natural-language search prompt |
limit | Optional maximum number of results |
Returns an array of matching data mart objects:
| Field | Description |
|---|---|
id | Data mart identifier |
title | Data mart name |
description | Data mart description |
url | Link to open the data mart in OWOX Data Marts |
relevance_score | How closely the data mart matches your question |
The response also includes project.id and project.title.
Only non-draft data marts visible to your project role are returned. An empty result usually means nothing matched the prompt; when you see no published data mart at all, the response also includes getting_started (see The assistant says there are no data marts) so the assistant explains what to do instead of rephrasing the search.
get_relevant_reports_by_prompt
Section titled “get_relevant_reports_by_prompt”Finds existing reports from a natural-language prompt, ranked by relevance. Use it when you refer to a report by name or subject — “open the revenue report”, “rerun the weekly ads export” — and its identifier is not yet known. The report name is matched first, then the names of its data mart and destination.
Input:
| Field | Description |
|---|---|
prompt | Natural-language search prompt |
limit | Optional maximum number of results, default 10 |
Returns an array of matching report objects:
| Field | Description |
|---|---|
report_id | Report identifier |
title | Report name |
data_mart | The report’s data mart — id, title |
destination | The destination the report exports to — id, title, type |
relevance_score | How closely the report matches your prompt |
url | Link that opens the report in OWOX Data Marts |
The response also includes project.id and project.title.
A report is returned when both its data mart and destination are visible to you under the project access rules, matching the Data Mart’s Destinations tab. You do not need to own a report to find it; permissions to edit or run it are checked separately. Use get_data_mart_reports when the data mart is already known and you need every report with its full definition.
get_data_mart_details_by_id
Section titled “get_data_mart_details_by_id”Returns field-level metadata for one data mart visible to you in the current project.
Input:
| Field | Description |
|---|---|
data_mart_id | Data mart identifier returned by list_data_marts or get_relevant_data_marts_by_prompt |
detail_level | Optional: native (default) returns only the data mart’s own fields; with_joined_fields additionally returns joined fields when the question truly requires them |
Returns:
| Field | Description |
|---|---|
id | Data mart identifier |
name | Data mart name |
url | Link to open the data mart in OWOX Data Marts |
description | Data mart description |
fields | The data mart’s own (native) output fields with query name, presentation displayName, types, descriptions, and business names when available. A field OWOX already computes for you also carries a usage note saying so |
joined_fields_included | Whether joined fields were requested and evaluated. When false, joined_fields was intentionally omitted rather than evaluated as empty. |
joined_fields | Fields contributed by blended/joined data marts when requested, each with exact query name, presentation displayName, source data mart, type, and allowed aggregations |
operators_by_category | For each field-type category present in the data mart (number/string/date/time/boolean/other), the query_data_mart filter/slice operators its fields accept |
Use this tool when you need to understand the fields available in a specific data mart. It returns native fields by default; request detail_level=with_joined_fields before concluding that the native schema cannot answer a question or after a field_not_found error. A field’s allowedAggregations and its category’s entry in operators_by_category tell the assistant which aggregations and operators the field supports. The assistant can build queries without trial and error. An empty allowedAggregations on a calculated field whose formula already aggregates means the value is already computed, not that the field is unusable — select it by name and read its usage note. It does not return sample values, data freshness, owners, or actual data rows. To learn how joined/blended fields are set up, see Joinable Data Marts.
query_data_mart (requires mcp:read and mcp:write)
Section titled “query_data_mart (requires mcp:read and mcp:write)”Runs a query against one data mart and returns its data rows, plus server-side totals computed over all matching rows. Unlike the tools above, this reads the data itself — each call runs against your warehouse and costs credits, and every call is recorded in Run History (the query definition and executed SQL only — never row values).
Input:
| Field | Description |
|---|---|
data_mart_id | Data mart to query |
fields | Exact field names to return, copied from get_data_mart_details_by_id. Must include every field used in aggregations, date_buckets, and sort. Reference blended fields by their qualified <alias>__<field> name |
aggregations | Aggregations over a field: SUM, COUNT, COUNT_DISTINCT, AVG, MIN, MAX, and percentiles P25/P50/P75/P95. Which of these a field allows depends on its type and per-field settings — use the allowedAggregations returned by get_data_mart_details_by_id. Group-by is implied by the non-aggregated fields |
date_buckets | Bucket a date/timestamp field by DAY/WEEK/MONTH/QUARTER/YEAR. Only date-category fields can be bucketed; time_zone applies only to types with a time component (not pure DATE) |
sort | Order the result rows: each rule is { field, direction } with direction asc or desc; rules apply in order (the first is the primary key). Each sorted field must also appear in fields |
slices | Pre-join filters — narrow a joined data mart before it is blended in (joined fields only) |
filters | Post-join filters on the blended result. Row-level predicates applied to raw values before any aggregation — there is no HAVING, so they cannot threshold an aggregated total. Which operators a field accepts depends on its type — see operators_by_category from get_data_mart_details_by_id; several filters combine with AND. in/not_in take an array of values (match any of / none of). The negative operators neq, not_contains, not_regex, and not_in are NULL-inclusive — they keep rows where the field is NULL, treating a missing value as “not equal to”; add an is_not_blank filter on the same field to exclude NULLs |
limit | Maximum rows to return (1–1000, default 20). There is no pagination |
For a “how many” question, use COUNT or COUNT_DISTINCT (when the user means unique entities) rather than returning raw rows and counting them in the assistant. Include only the dimensions needed for the requested breakdown.
When the data mart already defines the quantity being asked for as a calculated field that aggregates — a ROAS written as SUM(revenue) / NULLIF(SUM(adCost), 0), say — list that field in fields instead of pulling its inputs and dividing them in the reply. OWOX then computes it in the warehouse at the grain the question asks for, over every matching row rather than only the rows the limit let through.
Returns:
| Field | Description |
|---|---|
columns | Business-friendly headers matching the header row in rows |
column_metadata | Exact technical query name plus business-friendly display_name, type, and description when available |
rows | The data rows, as a compact header-once table |
returned_rows | Number of rows in the response |
truncated | true if not all matching rows were returned — narrow the query or raise limit |
truncation | Present only when truncated; reasons is row_limit, payload_byte_cap, or both |
totals | Server-side totals over all matching rows, ignoring the row limit |
data_last_updated | When the source tables behind this result last changed in the warehouse — see below |
source | The id, title, and OWOX link of the Data Mart that supplied the response |
calculation_origin | Marks rows as taken from OWOX, and totals and data_last_updated as produced by OWOX when available |
Only data marts and fields your project role permits are queryable. For more on how aggregations and totals are computed, see Report Aggregations and Totals; for why a given aggregation may be rejected on a field, see Report Output Controls.
When presenting results, the assistant must name the source Data Mart. It must distinguish OWOX-provided values from any arithmetic it performs itself. If truncated is true, it must explicitly tell the user that returned rows are incomplete; server-provided totals remain valid for all matching rows, but any number calculated from returned rows can be incomplete.
Data last updated
Section titled “Data last updated”data_last_updated answers “how current is what I am looking at?”. Each query measures it live, in the same call that reads the data. OWOX never caches this value and never bills it separately — the call’s own credits cover it. A non-blended query (no joined fields) also saves the measurement as the Data Mart’s last-known value. The same value appears across the OWOX UI — see Data Last Updated.
| Field | Description |
|---|---|
data_last_updated_at | ISO-8601 UTC time when the newest source table last changed, or null when the warehouse does not report it |
computed_at | When this measurement was taken |
coverage | complete, partial (some sources unreadable — the real time can only be more recent), or unavailable (nothing could be determined) |
sources | Per-table detail, each with its own time and an optional note explaining a gap |
Read the value precisely. It is a storage timestamp, not a statement about the data’s content:
- It says when something last wrote to the source tables. A backfill can rewrite a table today with figures from 2021, so “updated today” does not mean “covers today”. For this reason the field is data last updated, not freshness.
nullmeans unknown — neither fresh nor stale. The assistant should say OWOX could not determine it, without implying either.- With
coverage: "partial", treat the timestamp as “at least as recent as” and say the picture is incomplete. - The assistant is asked to present the timestamp in a business-friendly form (e.g. “August 4, 2026 at 09:46 UTC”) — converted to the user’s time zone when the conversation establishes one, otherwise in UTC with the zone named — never as a raw ISO-8601 string. The machine-readable ISO-8601 value stays in the structured response.
Coverage is best effort per storage. Google BigQuery, AWS Redshift, AWS Athena, Snowflake, and Databricks are supported. OWOX resolves views and SQL data marts through to their underlying base tables. Sharded and wildcard table sets collapse into one entry. Other storages currently report unavailable. sources deliberately omits views: a view’s own modification time reflects a change to its definition, not to any data. Redshift metadata can lag real writes by up to ~5 minutes. Older Redshift releases do not report modification times at all. Athena is exact for Iceberg tables; Hive tables report null with a note, because their catalog stores no data-change time. See Data Last Updated for storage-specific caveats.
list_destinations
Section titled “list_destinations”Lists the destinations in the current project — such as Google Sheets, Looker Studio, or messaging destinations — so the assistant knows where a report could be sent.
Returns an array of destination objects:
| Field | Description |
|---|---|
id | Destination identifier |
url | Link to open this destination in OWOX |
name | Destination name |
type | Destination type (for example google_sheets, looker_studio, slack, email, teams, google_chat) |
owner | The user who created the destination, or null when unavailable |
connectedGoogleAccount | For Google Sheets destinations, the Google account that completed OAuth consent |
createdAt | Destination creation timestamp |
The list reflects your access: it includes only the destinations your project role permits you to use. If you are identifying a Google Sheets destination just created through add_destination, match by connectedGoogleAccount, not by createdAt or “newest” — someone else can create a destination at the same time. To add or manage destinations, see Destination Management.
add_destination (requires mcp:write)
Section titled “add_destination (requires mcp:write)”Starts or completes setup for a report-delivery destination. The exact flow depends on destination_type.
Input:
| Field | Description |
|---|---|
destination_type | Destination type to connect or create: google_sheets, looker_studio, email, slack, teams, or google_chat |
title | Optional destination name. Applies to email, slack, teams, google_chat, and looker_studio; Google Sheets names are entered in the browser setup form |
emails | Required for email, slack, teams, and google_chat; target email addresses or delivery addresses for the destination |
Returns:
| Field | Description |
|---|---|
authorization_url | For google_sheets, a link to the OWOX “Connect Google Sheets” page where the user completes Google OAuth |
destination_id | New destination identifier. Returned for looker_studio, email, slack, teams, and google_chat; absent for Google Sheets until setup is completed |
destination_url | Link to open the created destination; absent for Google Sheets until OAuth creates it |
instructions | Human-readable next steps for finishing setup or using the new destination |
For google_sheets, this tool does not create the destination immediately. It returns a project-scoped setup link; the user opens it, signs in to OWOX if needed, clicks Connect with Google, and approves Google access. After the user confirms setup is complete, call list_destinations and match the new Google Sheets destination by connectedGoogleAccount. The created destination is usable by the person who connected it, but it starts unshared for other project members until someone shares it in the UI.
For email, slack, teams, and google_chat, the tool creates the destination directly and returns destination_id. For looker_studio, the tool also creates the destination directly, but it never sends connector credentials or secret keys through MCP/chat; the user opens the destination in OWOX Data Marts to copy those credentials, and the returned instructions include a link to the Data Studio destination guide with the full walkthrough.
get_data_mart_reports
Section titled “get_data_mart_reports”Lists the reports tied to a data mart, including each report’s destination, what it exports, the spreadsheet it writes to (Google Sheets), its run schedules (a report can have any number of schedule triggers), and its last run status.
Input:
| Field | Description |
|---|---|
data_mart_id | Data mart identifier |
Returns an array of report objects:
| Field | Description |
|---|---|
report_id | Report identifier |
report_url | Link to the report’s Data Mart reports page in OWOX |
data_mart_id | Data mart identifier |
name | Report name |
destination_id | Destination the report exports to |
destination_url | Link to the destination in OWOX |
destination_type | Destination type (for example google_sheets) |
owner | The user who created the report |
created_by_current_user | true when the connected user created the report |
created_at | Creation timestamp |
fields | Column names the report exports, or ["*"] for every field; [] is a metrics-only report that exports no dimension column, only its Unique Count metric(s) |
unique_count_sources | Unique Count metrics the report carries — unique_count for its own data mart, <source>__unique_count for joined sources. Set in the OWOX UI; update_report keeps them |
filters, slices | Row filters and pre-join filters applied on every run, in the same vocabulary add_report and update_report accept |
ui_only_filters | Present only when the report also applies rules created in the OWOX UI that the assistant cannot express — post-aggregation constraints, regex, calendar presets such as “today”. update_report keeps them untouched; change or remove them in the OWOX UI |
aggregations | Aggregations applied on every run, in add_report vocabulary (including the report-only STRING_AGG and ANY_VALUE) |
date_buckets | Date buckets applied on every run |
sort | Sort order of the exported rows |
limit | Max rows per run, or null when uncapped |
spreadsheet_id | Google Sheets only. Spreadsheet the report writes to — pass it as spreadsheet_id to add_report to put a related export into the same document |
sheet_url | Google Sheets only. Link to the report’s sheet |
schedules | Array of run schedules — trigger_id, cron_expression, time_zone, is_active, next_run_at, last_run_at |
last_run_at | Timestamp of the most recent run |
last_run_status | Status of the most recent run |
Use this tool before creating a report, to find one that already exports what you asked for, and before scheduling or changing a report’s cadence, to see what already exists.
run_report (requires mcp:write)
Section titled “run_report (requires mcp:write)”Starts an existing report run and delivers fresh data to its push destination. Use it for a later rerun, or to retry delivery when add_report returned initial_run.status: failed_to_queue. Do not call it for the initial run when add_report already returned a queued run_id. This returns immediately with identifiers for the run; it does not wait for completion. Each call starts a new billed Report Run, so do not call it again for the same report while the previous run is still running or pending.
Input:
| Field | Description |
|---|---|
report_id | Report to run, from get_data_mart_reports |
Returns:
| Field | Description |
|---|---|
report_id | Report identifier |
run_id | Run identifier to pass to get_report_run_status |
Use this tool for push destinations such as Google Sheets, Email, Slack, Microsoft Teams, and Google Chat. Pull-based destinations such as Looker Studio cannot be run through run_report.
get_report_run_status
Section titled “get_report_run_status”Checks the current status of a report run started with run_report or queued automatically by add_report.
Input:
| Field | Description |
|---|---|
report_id | Report identifier |
run_id | Run identifier returned by run_report |
Returns:
| Field | Description |
|---|---|
report_id | Report identifier |
run_id | Run identifier |
status | Normalized status: running, success, failed, cancelled, interrupted, or restricted |
should_poll | true when the assistant should keep checking this run; false when polling should stop |
stop_reason | queued_too_long, running_too_long, or null |
queued_at | Timestamp when the run was queued, if available |
started_at | Timestamp when execution started, if available |
raw_status | Backend run status |
error | Error message for failed runs, otherwise null |
message | Polling guidance for the assistant, including when a run is taking longer than usual or may be stuck; null when the run has reached a terminal status |
Report runs can take several minutes. While should_poll is true, the assistant should call get_report_run_status again, ideally waiting about 15 seconds between checks if the client supports waiting.
list_report_run_schedules
Section titled “list_report_run_schedules”Lists every scheduled report-run trigger in the current project that you can see, in a single response.
Returns an array of schedule objects:
| Field | Description |
|---|---|
trigger_id | Schedule identifier — pass to update_report_run_schedule or delete_report_run_schedule |
report | The report this schedule belongs to (id, title, url) |
data_mart | The data mart the report is built on (id, title, url) |
schedules_url | Link to the report schedules page in OWOX |
cron_expression | Schedule in 5-field cron syntax |
time_zone | IANA timezone the cron expression is evaluated in |
is_active | Whether the schedule is currently enabled |
next_run_at | Next scheduled run, if any |
last_run_at | Last run, if any |
can_edit | Whether you can update this schedule |
can_delete | Whether you can delete this schedule |
Use this tool to find a schedule’s trigger_id before updating or deleting it. Creating a new schedule (create_report_run_schedule) never replaces an existing one — a report can have several. These schedules are the same report triggers you can manage in the UI — see Report Triggers.
create_report_run_schedule (requires mcp:read and mcp:write)
Section titled “create_report_run_schedule (requires mcp:read and mcp:write)”Adds a new recurring run schedule to an existing report. The assistant translates natural language (for example “every Monday at 9am”) into a standard 5-field cron expression before calling this tool.
Input:
| Field | Description |
|---|---|
report_id | Report to attach the schedule to |
cron_expression | 5-field cron expression |
time_zone | Optional IANA timezone (for example Europe/Kyiv); defaults to UTC if not specified |
is_active | Optional; defaults to true |
Returns: trigger_id, report_id, cron_expression, time_zone, is_active, next_run_at.
This always creates an additional schedule — it never replaces or updates an existing one. To change an existing schedule, use update_report_run_schedule instead.
update_report_run_schedule (requires mcp:read and mcp:write)
Section titled “update_report_run_schedule (requires mcp:read and mcp:write)”Updates one existing schedule identified by trigger_id (from list_report_run_schedules).
Input:
| Field | Description |
|---|---|
trigger_id | Schedule to update |
cron_expression | New 5-field cron expression |
time_zone | Optional; omit to keep the schedule’s current timezone |
is_active | Optional; omit to keep the schedule’s current active state |
Returns: trigger_id, report_id, cron_expression, time_zone, is_active, next_run_at.
This changes the schedule’s cadence in place — it does not change which report it belongs to and does not create another schedule.
delete_report_run_schedule (requires mcp:read and mcp:write)
Section titled “delete_report_run_schedule (requires mcp:read and mcp:write)”Removes a single schedule identified by trigger_id. This is destructive and cannot be undone from the assistant.
Input:
| Field | Description |
|---|---|
trigger_id | Schedule to remove |
Returns: trigger_id, report_id, and schedule: null to confirm removal. Only that one schedule is removed — the report and any other schedules it has are left intact.
add_report (requires mcp:write)
Section titled “add_report (requires mcp:write)”Creates a report that exports a data mart to an existing destination (see list_destinations). This is how the assistant exports, saves, or delivers OWOX data — it does not copy query rows into files or documents of its own. For push destinations, it also queues the first run by default so the destination is populated immediately. Set run_immediately to false only when the user explicitly wants configuration without delivery, such as before creating a schedule.
One report per request: when you ask to change a report that already exists — add a filter, sort it differently, rename it — the assistant updates that report with update_report instead of creating another one. To keep a conversation from piling up duplicates, add_report refuses a report whose fields duplicate one you already created on the same data mart and destination: it returns error_code: similar_report_exists together with the existing report’s definition, and the assistant updates that report instead. If you really want a second, separate report, say so — the assistant then passes allow_similar: true.
- Google Sheets: a new Google Sheet is created automatically and linked to the report. The initial run then writes data into it by default. The file and its sheet both take the report’s name. Unlike every other tool, this path reaches outside OWOX: it creates a file in Google Drive and attempts to share it with you. When you ask for several related exports, the assistant passes the first report’s
spreadsheet_idto the nextadd_reportcalls, so each report becomes a separate sheet of the same document instead of a separate file; that sheet is named after its report too. See Google Sheets destination for how to set the destination up. - Looker Studio: the report is created with default settings (data cache lifetime of 5 minutes) — the tool accepts no Looker-Studio-specific parameters, and no
name(Looker Studio reports carry no name). Each data mart + destination pair can have exactly one Looker Studio report; creating a second one returns an error instead of a duplicate. Creating the report only makes the data mart available to the destination: data appears in a dashboard after you connect Looker Studio to OWOX with the destination’s JSON Config (it contains a secret key, so it is never sent through the assistant). The response includesinstructionsand asetup_guide_urlso the assistant can walk you through it; the full guide is Data Studio destination. If the project has no Looker Studio destination yet, the assistant can create one withadd_destinationfirst. - Email, Slack, Microsoft Teams, Google Chat: the report carries the message subject and body; the recipients or channels are configured on the destination itself, not on the report. The default initial run sends the rendered message immediately. The send condition is always the default (“Send always”) — change it in the OWOX Data Marts UI if you need a conditional report.
Input:
| Field | Description |
|---|---|
data_mart_id | Data mart to export |
destination_id | The destination to export to (from list_destinations) |
fields | Exact column names to include, or ["*"] for every field |
filters | Optional. Row filters applied on every report run — same shape and operator vocabulary as query_data_mart’s filters, so the assistant can create a report that exports exactly the filtered result you were looking at. A filter may reference a field that is not in fields. Omit to export all rows |
slices | Optional. Pre-join filters that narrow a joined data mart before blending — same as query_data_mart’s slices. Blended data marts only |
aggregations | Optional. Aggregations applied on every run — same as query_data_mart’s aggregations, plus the report-only STRING_AGG and ANY_VALUE. Each aggregated field must also appear in fields; other fields become group-by dimensions |
date_buckets | Optional. Bucket a date/timestamp field by DAY/WEEK/MONTH/QUARTER/YEAR — same as query_data_mart’s date_buckets. Each bucketed field must also appear in fields |
sort | Optional. Order of the exported rows — same as query_data_mart’s sort |
limit | Optional. Max rows each run exports; omit for no cap (the interactive query limit is deliberately NOT carried over) |
name | Report name — also the new sheet’s title (Google Sheets) and the default message subject (email family). Required for those destination types; not accepted for Looker Studio |
message | Message settings — required for email, Slack, Teams, and Google Chat destinations, rejected for other types |
message.subject | Optional message subject or heading. Defaults to the report name |
message.body | Message body template. Supports the {{table}} placeholder, which renders the report’s result table |
run_immediately | Optional. Defaults to true for push destinations, which starts one billed Report Run and delivers data. Set false for configuration-only creation. Looker Studio is pull-based: omit this field or set it to false; true is rejected |
spreadsheet_id | Optional, Google Sheets only. Add the report as a new sheet of this existing spreadsheet (from an earlier add_report result or get_data_mart_reports) instead of creating a new file. The destination’s connected Google account needs edit access, a sheet with the report’s name must not exist yet, and the spreadsheet must be shared with you — one confirmed not to be is refused |
allow_similar | Optional. Create the report even though you already have one exporting the same fields from this data mart to this destination. Without it, such a call returns error_code: similar_report_exists |
Returns:
| Field | Description |
|---|---|
report_id | Report identifier |
destination_type | Type of the destination the report was created for |
report_url | Link to the report in OWOX Data Marts |
spreadsheet_id | Google Sheets only. Spreadsheet the report writes to — reuse it to add related exports as sheets of the same document |
sheet_url | Google Sheets only. Link to the report’s sheet |
owner | The user who created the report |
status | created |
initial_run | Outcome of the first run: queued, not_requested, not_applicable, or failed_to_queue. The report exists for every outcome |
initial_run.run_id | Present for queued; pass it with report_id to get_report_run_status and do not call run_report again for this initial run |
initial_run.should_poll | true only for queued; poll until the status tool returns should_poll: false |
placed_in_root | Google Sheets only, new files only. true if the configured Drive folder could not be used, so the sheet was created in the Drive root |
shared_with_requester | Google Sheets only. New file: false if the sheet could not be shared with you. Existing spreadsheet: false if your access to it could not be confirmed (it is never granted). Either way, opening the link may require requesting access |
instructions | Looker Studio only. What has to happen before dashboard data flows — the assistant relays this to you |
setup_guide_url | Looker Studio only. Link to the step-by-step Looker Studio connection guide |
update_report (requires mcp:write)
Section titled “update_report (requires mcp:write)”Updates an existing report: renames it, replaces which data mart fields it exports, replaces its output controls (filters/slices, aggregations, date buckets, sort, limit — same vocabulary as query_data_mart), and/or — for reports with an email, Slack, Teams, or Google Chat destination — changes the message subject or body. Anything not provided stays unchanged — the destination, owners, schedules, and send condition are preserved as-is. This is the tool the assistant uses when you ask to change a report it created earlier in the conversation.
By default, a Google Sheets report is run again after an update that actually changed what it exports, so the sheet reflects the new definition; a name-only or message-only change, or re-sending the same controls, does not trigger a run. Email, Slack, Microsoft Teams, and Google Chat reports are not re-sent by an update — a run would deliver the message to every recipient or channel — unless you explicitly ask to send it now. The response returns the report as it is after the update.
Input:
| Field | Description |
|---|---|
report_id | Report to update (from get_data_mart_reports) |
fields | Optional. Replacement column selection, or ["*"] for every field |
filters | Optional. Replacement row filters (same vocabulary as query_data_mart’s filters). Replaces only the current row filters the assistant can express — stored slices and ui_only_filters are untouched; [] removes every expressible row filter |
slices | Optional. Replacement pre-join filters (blended data marts only). Replaces only the current slices the assistant can express — stored row filters and ui_only_filters are untouched; [] removes every expressible slice |
aggregations | Optional. Replacement aggregations (including the report-only STRING_AGG and ANY_VALUE); replaces the whole list, so copy the ones to keep from get_data_mart_reports; [] removes them |
date_buckets | Optional. Replacement date buckets; [] removes them |
sort | Optional. Replacement sort order; [] removes it |
limit | Optional. New max rows per run; null removes the cap |
name | Optional. New report name |
message | Optional. Message changes — only for reports with an email-family destination, rejected for other types |
message.subject | Optional. New message subject or heading |
message.body | Optional. New message body template (supports {{table}}). Replaces the current body; if the report used an insight template, it switches to this custom message |
run_immediately | Optional. Omit for the default (re-run a Google Sheets report when the export changed; no run for a name-only or message-only change; email-family reports are never re-sent by default). false updates a Google Sheets report without refreshing it; true re-delivers, including re-sending an email-family report. Looker Studio is pull-based: true is rejected |
At least one change parameter must be provided (and message, when present, needs subject and/or body); run_immediately alone is not a change.
Returns:
| Field | Description |
|---|---|
report_id | Report identifier |
status | updated |
destination_type | Type of the report’s destination |
name | Report name after the update |
fields, filters, slices, aggregations, date_buckets, sort, limit | The report’s definition after the update — the same shape get_data_mart_reports returns |
spreadsheet_id, sheet_url | Google Sheets only. The spreadsheet and sheet the report writes to |
run | Outcome of the refresh run: queued (with run_id to poll), not_requested, not_applicable, or failed_to_queue. The update is saved for every outcome |
delete_report (requires mcp:write)
Section titled “delete_report (requires mcp:write)”Deletes a report. The report stops running and disappears from the project; the underlying data mart, destination, and any already-exported documents are not affected. This cannot be undone, so your assistant asks for confirmation before calling it.
Input:
| Field | Description |
|---|---|
report_id | Report to delete (from get_data_mart_reports) |
Returns:
| Field | Description |
|---|---|
report_id | Report identifier |
status | deleted |
What costs credits
Section titled “What costs credits”Most of what you ask costs nothing. These actions consume credits:
query_data_mart— reads actual data rows. Each successful call counts as one Report Run, billed as an MCP Query Run.run_report— starts a Report Run that delivers data to a destination.add_reportwith its default initial run — creating the report is free, but the automatically queued run consumes one Report Run. Setrun_immediately: falsefor configuration-only creation without that run.
Everything else is free. Listing data marts, inspecting fields, browsing destinations, reading reports and schedules, and checking run status only read metadata. Creating a destination, report, or schedule is also free; add_report itself is free when run_immediately is false or the destination is pull-based. You pay when the report runs, not when you set it up.
Four things to expect:
- Cost does not depend on size. One call costs the same whether it returns 20 rows or 1,000. Ask one broad question rather than several narrow ones.
- One question can cost several credits. The assistant may run several queries to answer you — for example, one per month you asked about. Ask it to plan the queries first if you want to keep the count down.
- Failed queries are free. If a query fails, times out, or you cancel it, you pay nothing. A wrong guess about a field name costs nothing either.
- Running out of credits blocks queries only. The metadata tools keep working, so the assistant can still explore your catalog.
How to use it: example prompts
Section titled “How to use it: example prompts”Once the OWOX server is connected, just ask your assistant in plain language. You do not need to name the tools — the assistant calls them for you. Prompts marked (costs credits) read or deliver actual data — see What costs credits. Try prompts like:
- “Which OWOX project am I connected to, and what is my role in it?”
- “What data is available in this project, and what should I ask next?”
- “List all the data marts in my project.”
- “Which of my data marts were updated most recently?”
- “Do I have any data marts about Facebook Ads? Show their descriptions.”
- “What fields are available in the Facebook Ads data mart?”
- “Give me a one-line summary of each data mart and what it is for.”
- “What’s the total revenue by month in the Sales data mart?” (costs credits)
- “Show the top campaigns by spend in the Ads data mart.” (costs credits)
- “Which destinations can I send a report to?”
- “Connect a Google Sheets destination for my account.”
- “Create an email destination for
analytics-alerts@example.com.” - “What reports and schedules already exist for the Sales data mart?”
- “Run the Weekly Ads Report now and tell me when it finishes.” (costs credits)
- “Export the Ads data mart to a new Google Sheet called ‘Weekly Ads Report’ and tell me when the initial run finishes.” (costs credits)
- “Add a filter to that report so it only includes paid channels.” (costs credits; the report is updated and refreshed, not duplicated)
- “Export the ad spend by source into the same spreadsheet as a second sheet.” (costs credits)
- “Create a Looker Studio report from the Sales data mart with all fields.”
- “Send the daily revenue table to the Alerts Slack destination with the message ‘Yesterday’s numbers’.” (costs credits; sends immediately)
- “Rename that report to ‘Q3 Ads Report’ and keep only the campaign and spend fields.”
- “Change the subject of the daily Slack report to ‘Morning numbers’.”
- “Schedule that report to run every Monday at 9am New York time.”
- “Turn off the schedule you just created.”
- “Delete the old ‘Test export’ report from the Sales data mart.”
What these tools can and cannot do: They let the assistant discover your project, summarize the published data mart catalog, inspect data mart metadata, list destinations, list reports and schedules, and check report-run status. With
query_data_mart, the assistant can run a bounded structured query and read the resulting data rows and totals; this is billable and recorded in Run History. With your confirmation, the assistant can also create destinations (add_destination), create a report for a Google Sheets, Looker Studio, email, Slack, Microsoft Teams, or Google Chat destination — optionally with the same filters, slices, aggregations, date buckets, and sort as aquery_data_martcall, so the export matches the numbers you saw (add_report). New push-destination reports run once by default and return arun_idto poll;run_immediately: falsecreates configuration only. Related Google Sheets exports can share one spreadsheet as separate sheets. The assistant can also rename a report, change which fields it exports, replace its output controls, or edit the message of email-family reports (update_report) — it does this, rather than creating a second report, when you ask to change one that exists — delete a report (delete_report), create, update, or delete report-run schedules, and start a later manual run for supported push-destination reports (run_report). They cannot run arbitrary SQL — only structured queries built from the fields, filters, and aggregations described above — and cannot edit a data mart, edit an existing destination, change project settings, retrieve destination secret keys, or run pull-based Looker Studio reports throughrun_report.What is shared with your AI provider: To answer your prompts, the project description and other project metadata, data-mart metadata, destination metadata, report and schedule metadata, report-run status, and your project roles can be sent to the AI provider behind your client, such as Anthropic for Claude or OpenAI for ChatGPT. If you ask the assistant to create an email-based destination, the email addresses you provide are also sent through that client. Whenever the assistant runs
query_data_mart, the resulting data rows and totals are sent to that provider so it can answer with the data — only data you are permitted to query. Connect OWOX only to clients your organization permits to receive this information.
Troubleshooting
Section titled “Troubleshooting”Requests return 401 Unauthorized
Section titled “Requests return 401 Unauthorized”The MCP server rejects a request with 401 in these cases. Your AI client may surface these as a generic “couldn’t connect” or “authorization expired” message rather than the exact text below:
| Message | Cause | Fix |
|---|---|---|
Missing MCP bearer token | No Authorization: Bearer header was sent. | Re-run authorization so the client obtains a token. A GET /mcp without a token (a client probe) is expected and harmless. |
Invalid MCP bearer token | The token is expired, revoked, or invalid. | Disconnect and reconnect the MCP server to obtain a fresh token. |
Invalid MCP resource | The token was issued for a different MCP server URL than this request. | Confirm the client points to the same /mcp URL used during authorization, then reconnect. |
Invalid MCP project context | A project-specific server URL does not match the project in the token. | Disconnect and reconnect using the project-specific URL for the target project. |
Missing MCP project context / Missing MCP project roles | The token has no project selected or no active role in it. | Reconnect and make sure you select a project, or use a project-specific URL for a project where you are an active member. |
A tool reports Missing MCP scope: mcp:write
Section titled “A tool reports Missing MCP scope: mcp:write”The token does not include the write scope required for tools that create, change, run, or bill something. Disconnect and reconnect the MCP server, then approve the requested scopes during authorization. If your client lets you choose scopes manually, include both mcp:read and mcp:write.
The assistant says there are no data marts
Section titled “The assistant says there are no data marts”MCP works only with published data marts that your project role lets you see. When there is none, list_data_marts, get_relevant_data_marts_by_prompt, and summarize_data_catalog return getting_started instead of a bare empty list, and the assistant explains what a data mart is and what to do next rather than retrying the search or querying data:
| Field | Description |
|---|---|
can_create_data_marts | Whether your role may create data marts (Project Admin or Technical User) |
create_data_mart_url | The page in OWOX Data Marts where a new data mart is created |
data_marts_url | The Data Marts list of the connected project |
guides | Links to the core concepts, connector-based, and SQL-based data mart guides |
draft_data_marts | Draft data marts you can see; they become available to MCP once published |
instructions | Internal guidance the assistant relays to you |
A data mart cannot be created or published through MCP. To continue:
- Project Admin or Technical User: open
create_data_mart_url, connect a data source or define the data mart from SQL, a table, or a view on a connected storage, then save and Publish it. If the assistant lists drafts, open each one, finish its setup, and publish it. - Business User: ask a Project Admin or a Technical User of the project to create and publish a data mart and share it with you for reporting.
Then ask the assistant again — no reconnection is needed.
The wrong project is connected
Section titled “The wrong project is connected”Project selection is fixed at authorization time. See Switch projects or disconnect for how to reconnect and choose a different project or use another project-specific URL.
A query_data_mart call fails
Section titled “A query_data_mart call fails”A failed query costs nothing — OWOX bills a call only after it succeeds. This covers queries that time out, queries you cancel, and queries the credit limit blocks.
If the assistant reports that the project is out of credits, query_data_mart has hit its credit limit — upgrade the plan to keep querying (the read-only tools keep working). If it says a field wasn’t found, it likely guessed a field name; ask it to check the data mart’s fields first with get_data_mart_details_by_id, then re-run the query.
A Google Sheets destination created through add_destination is missing
Section titled “A Google Sheets destination created through add_destination is missing”For Google Sheets, add_destination only returns a setup link; the destination appears after the user opens the link and completes Google OAuth. Make sure the user signed in to OWOX with the same account that connected MCP, completed the browser flow, and has access to the project. Then call list_destinations and match the destination by connectedGoogleAccount. Do not pick the newest destination by createdAt.
A run_report call fails
Section titled “A run_report call fails”If the report uses a pull-based destination such as Looker Studio, it cannot be started through run_report. If the error says the report is already running or pending, use get_report_run_status for the existing run_id if you have it, or check Run History in OWOX Data Marts before starting another run.
add_report returns initial_run.status: failed_to_queue
Section titled “add_report returns initial_run.status: failed_to_queue”The report was created successfully, but its first run was not queued. Do not call add_report again because that would create a duplicate report and, for Google Sheets, another file. Call run_report once with the returned report_id, then poll get_report_run_status with its run_id. The same applies when update_report returns run.status: failed_to_queue — the update is saved; retry delivery with run_report.
add_report returns error_code: similar_report_exists
Section titled “add_report returns error_code: similar_report_exists”Nothing was created: you already have a report exporting the same fields from this data mart to this destination, and the response carries it under existing_report. Ask the assistant to change that report instead (it calls update_report), or say explicitly that you want a separate report — the assistant then retries with allow_similar: true.
add_report with spreadsheet_id fails to open the spreadsheet
Section titled “add_report with spreadsheet_id fails to open the spreadsheet”The destination’s connected Google account must be able to edit the spreadsheet. Share the spreadsheet with that account (see Google Sheets destination), or omit spreadsheet_id to create a new file. A sheet with the report’s name must not exist yet in that spreadsheet — pick another report name if it does.