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GTM API ships a managed MCP server at https://mcp.gtm-api.com/mcp. It exposes 160+ typed tools across 10 toolsets, so Claude, Cursor, ChatGPT or a custom agent runtime can search, connect, message and enrich on a LinkedIn account you own. MCP and REST are the same contract. Every tool maps 1:1 to an endpoint in the API reference: one Zod schema defines the tool, the endpoint and this documentation, so an agent and your backend code see identical shapes. If you can do it over REST, an agent can do it over MCP, under the same server-side safety layer.

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What the tools cover

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Guardrails that matter for agents

  • Preview then confirm. Outward actions (sends, bulk dispatches) return a preview and require an explicit confirmation step before anything reaches LinkedIn, so an over-eager agent cannot burn an account on its own.
  • Server-side limits. Per-action daily budgets are checked before dispatch, under every tool call. The agent does not need to count; the server refuses when a budget is spent.
  • Typed errors. Tools fail with the same 16-code taxonomy as REST, with recoverable and a suggestion field written for an LLM to act on.

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Where to go

Connect a client

Claude, Cursor, and anything else that speaks MCP.

Search these docs from AI tools

The documentation’s own MCP endpoint.
The public interface, connect examples and safety notes also live in the open repository: github.com/gtm-api/linkedin-mcp.