Manage data pipelines over PostHog MCP
Contents
The PostHog MCP server gives AI agents and MCP clients direct access to your pipelines. Because pipeline functions are just code plus configuration, this is one of the places MCP pays off most – an agent can write a transformation, test it against a real event, read the failure, and fix it, all without you opening the web app.
What you can do here
Build and edit functions. Create a destination, transformation, source webhook, or web script from scratch or from a template, then update it in place. Agents can generate the Hog code, the input schema, and the event filters together.
Browse templates. List the available function templates and retrieve one to see its inputs before building on top of it.
Test before shipping. Test-invoke a function against a real recent event and read back the request it would have sent. Nothing is delivered, so it's safe to iterate.
Debug what's already running. Pull a function's logs and metrics to see successes, failures, and filtered events, then patch the function based on what you find.
Control ordering and state. Reorder transformation execution, and enable or disable a function without deleting it.
Manage batch exports. List, create, update, and delete batch exports, and request file downloads for exported data.
Example prompts
List my active destinations and tell me which ones are failing.Create a transformation that drops events where test_mode is true.Test-invoke my Slack destination against a recent event and show me the payload.Show me the logs for my HubSpot destination from the last hour.Move my PII redaction transformation to run before everything else.Disable the destination that's erroring the most.
Install the MCP server
The recommended way is the AI wizard, which supports Claude, Cursor, Windsurf, VS Code, and more:
You can also configure it manually. See the MCP server documentation for the full tool list and scopes.
Related
- Build and monitor the same pipelines in the web app.
- Manage them from your own systems with the API.
- Learn the language behind pipeline functions in the Hog reference.