MCP server - gtm-api

GTM API ships a managed MCP server at https://mcp.gtm-api.com/mcp. It exposes 281 typed tools across 18 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.

What the tools cover

Area	Examples
Messaging	send a message, voice message or InMail, search and sync the inbox
Network	send, accept, withdraw or ignore connection requests, list connections and followers
Content	track posts and their metrics, comment, react, pull engagers
Enrichment	lite and full profiles, experience, skills, education, company data
Search	people, companies and posts, similar profiles, employees, decision-makers
Account health	smart limits, health snapshots, quota, block and activity logs
Infrastructure	anti-detect cloud browsers, dedicated proxies, webhooks

What to ask

Once a client is connected, the agent picks the tools itself from a plain request. A few that work on day one, each mapping onto the areas above:

Ask	What the agent does
”Show my latest LinkedIn conversations”	reads the synced inbox across your connected accounts, newest first
”Find decision-makers at fintech companies in Berlin”	runs a people search with the title, industry and location filters, returns the profiles
”Send connection requests to these 20 people, a few a day”	previews the batch, then dispatches it as a paced mass action under the account’s daily budget
”Reply to everyone who wrote back this week”	lists the threads with a new inbound message, drafts a reply per thread and sends after your confirmation
”Who liked my last post? Enrich them and keep the founders”	pulls the post’s engagers, enriches each profile, filters by title
”Which of my connections changed jobs this month?“	compares the synced connections against fresh profile data and lists the movers
”Draft a follow-up for everyone who did not answer in 5 days”	finds the outbound threads with no reply after five days and drafts the next message for each
”How is my account health, am I close to any limit?“	reads the account’s health snapshot and today’s spend against every smart limit

Anything that sends (a message, an invitation, a bulk run) goes through the preview and confirm step below; reads run straight away. The wording does not matter, the tools do: every row here is one or two tools from the API reference, chosen by the agent.

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.

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.

​What the tools cover

​What to ask

​Guardrails that matter for agents

​Where to go