> For the complete documentation index, see [llms.txt](https://docs.zenlytic.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zenlytic.com/mcp.md).

# MCP

- [MCP Overview](https://docs.zenlytic.com/mcp/overview.md): Connect your AI tools in to Zenlytic, or connect Zoë out to the rest of your stack.
- [MCP Server](https://docs.zenlytic.com/mcp/connecting-to-zenlytic.md): Connect AI tools like Claude.ai, Claude Code, and ChatGPT to Zenlytic's MCP server so they can query your business data directly.
- [Claude.ai](https://docs.zenlytic.com/mcp/connecting-to-zenlytic/claude-ai.md): Connect Claude.ai to Zenlytic's MCP server so Claude can query your business data directly.
- [Claude Code](https://docs.zenlytic.com/mcp/connecting-to-zenlytic/claude-code.md): Connect Claude Code to Zenlytic's MCP server so it can query your business data directly from the command line.
- [MCP Client](https://docs.zenlytic.com/mcp/client.md): Connect Zoë to remote MCP servers to call external tools directly from chat.
- [Google Workspace](https://docs.zenlytic.com/mcp/client/google-workspace.md): Connect Zoë to Google's Drive, Docs, Sheets, and Slides MCP servers so each user can work with their own Workspace files from chat.
- [Tableau](https://docs.zenlytic.com/mcp/client/tableau.md): Connect Zoë to Tableau's MCP server to browse workbooks, data sources, and metadata from chat.
- [Power BI](https://docs.zenlytic.com/mcp/client/powerbi.md): Connect Zoë to a Power BI MCP server to explore workspaces, datasets, and reports from chat.
- [Google](https://docs.zenlytic.com/mcp/client/google.md): Connect Zoë to Google's BigQuery MCP server to inspect schemas and run SQL from chat.
- [Looker](https://docs.zenlytic.com/mcp/client/looker.md): Connect Zoë to Looker's MCP server to query semantic models, dashboards, and metadata from chat.
- [dbt](https://docs.zenlytic.com/mcp/client/dbt.md): Connect Zoë to dbt's MCP server to explore models, metrics, exposures, and lineage from chat.
- [Atlan](https://docs.zenlytic.com/mcp/client/atlan.md): Connect Zoë to Atlan's MCP server to search data assets, glossaries, and lineage from chat.
- [Snowflake](https://docs.zenlytic.com/mcp/client/snowflake.md): Connect Zoë to Snowflake's MCP server to query Cortex tools, SQL, and custom functions from chat.
- [Reltio](https://docs.zenlytic.com/mcp/client/reltio.md): Connect Zoë to Reltio's MCP server to search entities, relationships, and AgentFlow tools from chat.
- [Github](https://docs.zenlytic.com/mcp/client/github.md): Connect Zoë to GitHub's MCP server to browse repos, issues, pull requests, and Actions from chat.
- [Jira](https://docs.zenlytic.com/mcp/client/jira.md): Connect Zoë to Jira's MCP server to search issues, run JQL, and work with Atlassian content.


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.zenlytic.com/mcp.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.