Pipecorn MCP server

The Pipecorn MCP server lets AI assistants and agents use Pipecorn directly through the Model Context Protocol. Once connected, your assistant can find companies, search leads, enrich contacts, manage Sales Navigator lists, and pull buying signals on your behalf, using the same data and credits as the REST API. Building an integration and only need your assistant to read these docs? Use the docs MCP server at https://docs.pipecorn.com/mcp instead. It needs no key and spends no credits.

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Set up your client

Any other MCP client that supports custom headers can connect the same way Claude Code and Cursor do: point it at the server URL and send your API key in the X-API-Key header (or a workspace key in X-Workspace-Key).

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Authentication

The server accepts exactly one of these on each request: Do not put an API key in Authorization. A Bearer value is always treated as an OAuth access token, so a raw API key there is rejected with 401 and "Invalid or expired token".

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Prerequisites

• A Pipecorn account with an API key (personal, or a workspace key). OAuth clients sign in with your Pipecorn login instead and do not need the key.
• Node.js, only for clients that run the server through mcp-remote (Claude Code, Cursor).

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How it fits with the other surfaces

The MCP server exposes the same primitives as the REST API and the CLI, so anything you can do in a chat you can also script. Use MCP when a person is driving an assistant. Use the API or CLI when code is driving the workflow. Credits and plan limits are shared across all three; see Credits vs limits. Before any large extraction or enrichment, the assistant should call the preview_* tools and get_credits to size the job and confirm the balance. The agents guide lists the conventions we recommend agents follow.

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Roadmap

The MCP server is updated regularly. Upcoming work:

• Additional tools for Signals and Lists
• CSV download support
• Custom UI cards
• Token-usage optimizations