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Documentation Index

Fetch the complete documentation index at: https://docs.lightdash.com/llms.txt

Use this file to discover all available pages before exploring further.

MCP server support for AI agents is in Beta.
Connect external Model Context Protocol (MCP) servers to your AI agents so they can take action in the tools your team already uses — like creating Linear issues, reading Notion pages, or searching Confluence — alongside their built-in Lightdash data tools.
MCP servers list in project settings showing a Linear MCP server with OAuth and a Lightdash docs server with no auth, both connected

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What you can do

Once an MCP server is connected to an agent, the agent can use its tools as part of any conversation. Common examples:
  • Notion — search docs, read pages, and create new pages from agent findings
  • Linear — file issues from anomalies the agent spots, comment on tickets, query project status
  • Confluence — search the knowledge base for context before answering, or publish summaries
  • Any other service that exposes a remote MCP server (GitHub, Jira, Slack, internal tooling, etc.)
The agent decides when to call MCP tools based on the user’s question and the agent’s instructions, the same way it decides when to query your data.

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Add an MCP server

MCP servers are configured per project and can be attached to one or more agents in that project.
1

Open AI agent settings

Go to Settings → AI agents → MCP servers for the project.
2

Add a new server

Click Add MCP server and provide:
  • Name — a friendly label (e.g. Notion, Linear)
  • URL — the remote MCP server endpoint (e.g. https://mcp.notion.com/mcp)
  • Auth type — None, Bearer token, or OAuth
3

Provide credentials

Depending on the auth type:
  • Bearer token — paste the token. It is encrypted at rest.
  • OAuth — click Connect to start the OAuth flow with the provider. Lightdash handles token storage and refresh.
  • None — no credentials required.
4

Attach to an agent

Edit any agent in the project and select the MCP server under MCP servers. The agent will now have access to that server’s tools.

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How credentials work

  • MCP servers live at the project level and can be reused across any number of agents in that project — configure once, attach anywhere.
  • Every user chatting with an agent uses the same configured credentials for that MCP server. Actions taken in the external tool (e.g. a Linear issue created by the agent) are attributed to whoever owns those credentials, not the end user.
  • Choose credentials with a scope that matches what you want the agent to do — for example, a service account for a shared Notion workspace, or a bot user for Linear.
Per-user OAuth (where each user connects their own account) is planned but not yet supported.

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Example agents

Product analytics agent + Linear
“Daily active users dropped 12% yesterday. File a Linear issue for the growth team with the breakdown by platform.”
The agent queries your data, summarizes the drop, and creates a Linear ticket with the chart and breakdown attached. Support insights agent + Notion
“Summarize this week’s top support themes and add it to our weekly review page in Notion.”
The agent pulls the data from your warehouse, generates the summary, and appends it to the right Notion page. RevOps agent + Confluence
“Before answering questions about pipeline definitions, check our Confluence runbook.”
The agent searches Confluence for the canonical definition, then answers using both the doc and your data.

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Security

  • All credentials (bearer tokens and OAuth tokens) are encrypted at rest.
  • OAuth refresh is handled automatically; expired tokens trigger a re-authorization prompt.
  • MCP servers are configured at the project level and only available to agents in that project.