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Pearch MCP Server

@Pearch-ai

Basic information

Category

Other

Transports

stdio

Author

Pearch-ai

Submitted by

Maksim Zvegintsev

About Pearch MCP Server

The most accurate people search API/MCP. Natural language in, high-quality candidates out. Built for ATSs and AI Agents.

#people-search#talent-discovery#pearch

Pearch MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "Pearch.ai": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "fastmcp",
        "fastmcp",
        "run",
        "your_path/pearch_mcp.py"
      ],
      "env": {
        "PEARCH_API_KEY": "your_token"
      }
    }
  }
}

Pearch MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Pearch?

Pearch is a people search API and MCP server that delivers precise candidate results from natural language queries. It integrates with any ATS or hiring platform and is designed for recruiters seeking high-quality sourcing backed by scientific methods.

How to use Pearch?

Install via Smithery (npx -y @smithery/cli install @Pearch-ai/mcp_pearch --client claude) or manually with Python 3.7+ and FastMCP. Set the PEARCH_API_KEY environment variable, then run fastmcp install pearch_mcp.py for standard use or fastmcp dev pearch_mcp.py for local development.

Key features of Pearch

  • Natural language candidate queries
  • Highest precision people search results
  • Backed by scientific evaluation methods
  • Seamless integration with any ATS
  • Trusted by recruiters as top-quality sourcing tool

Use cases of Pearch

  • Finding top candidates for open positions using natural language
  • Integrating high-quality sourcing into existing ATS workflows
  • Replacing manual Boolean search with conversational queries
  • Evaluating candidate pools quickly during talent acquisition

Frequently asked questions

1

What prerequisites are required to use Pearch?

Python 3.7 or newer, a Pearch.ai API key, and the FastMCP package.

2

How do I obtain a Pearch API key?

Visit the [Pearch.ai Dashboard](https://s.pearch.ai/settings) to get your API key, then set it as the `PEARCH_API_KEY` environment variable.

3

How can I install Pearch for Claude Desktop?

Use Smithery: `npx -y @smithery/cli install @Pearch-ai/mcp_pearch --client claude`. Alternatively, follow the manual Python installation steps in the README.

4

Can I run Pearch in development mode?

Yes. Set your API key, then run `fastmcp dev pearch_mcp.py` to start a local development server.

5

Where can I get support for Pearch?

Open an issue in the repository or contact support at f@pearch.ai.

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