Pearch
Best people search engine that reduces the time spent on talent discovery.
Pearch.ai MCP
MCP server for Pearch.AI: natural-language search over people and companies/leads (B2B). Use it from Cursor, Claude Desktop, VS Code, or any MCP-compatible client.
Evaluating AI Recruitment Sourcing Tools by Human Preference
Features
- search_people — natural-language search for people (e.g. “software engineers in California with 5+ years Python”); returns candidates with optional insights and profile scoring.
- search_company_leads — find companies and leads/contacts within them (B2B); e.g. “AI startups in SF, 50–200 employees” + “CTOs and engineering managers”.
- Test key by default — works out of the box with
test_mcp_key(masked/sample results); set your own key for full results.
Prerequisites
- Python 3.10+
- uv (recommended; Linux/macOS:
curl -LsSf https://astral.sh/uv/install.sh | sh) or pip - FastMCP — install with
pip install fastmcporuv add fastmcp
API key
Use test_mcp_key for masked (sample) results — no sign-up required.
For full, unmasked results, get an API key from the Pearch.ai Dashboard and set it as PEARCH_API_KEY in your MCP config (see Installation below).
Installation
Clone the repo, then follow the steps for your client:
git clone https://github.com/Pearch-ai/mcp_pearch
cd mcp_pearch
Claude Desktop
Automatic:
fastmcp install claude-desktop pearch_mcp.py --env PEARCH_API_KEY=test_mcp_key
Replace test_mcp_key with your dashboard key for full results.
If you see bad interpreter: No such file or directory (e.g. with conda), run:
pip install --force-reinstall fastmcp
or:
python -m fastmcp install claude-desktop pearch_mcp.py --env PEARCH_API_KEY=test_mcp_key
Manual: edit ~/.claude/claude_desktop_config.json and add under mcpServers. Replace /path/to/mcp_pearch with your actual path.
With uv:
"Pearch.ai": {
"command": "uv",
"args": ["run", "--with", "fastmcp", "fastmcp", "run", "/path/to/mcp_pearch/pearch_mcp.py"],
"env": { "PEARCH_API_KEY": "test_mcp_key" }
}
With pip/conda (no uv):
"Pearch.ai": {
"command": "python",
"args": ["/path/to/mcp_pearch/pearch_mcp.py"],
"env": { "PEARCH_API_KEY": "test_mcp_key" }
}
Ensure fastmcp is installed: pip install fastmcp.
Cursor
Recommended (automatic):
fastmcp install cursor pearch_mcp.py --env PEARCH_API_KEY=test_mcp_key
Replace test_mcp_key with your dashboard key for full results.
Manual: add to ~/.cursor/mcp.json (or project .cursor/mcp.json):
{
"mcpServers": {
"Pearch.ai": {
"command": "uv",
"args": ["run", "--with", "fastmcp", "fastmcp", "run", "/absolute/path/to/pearch_mcp.py"],
"env": { "PEARCH_API_KEY": "test_mcp_key" }
}
}
}
Replace /absolute/path/to/pearch_mcp.py with the real path. Use test_mcp_key for masked results, or your dashboard key for full results.
To generate a ready snippet:
fastmcp install mcp-json pearch_mcp.py --name "Pearch.ai"
Then paste the output into mcpServers in ~/.cursor/mcp.json.
VS Code and other clients
- VS Code: add the same
mcpServersblock to.vscode/mcp.jsonin your workspace. - Other MCP clients: use the same
command/args/envformat in the client’s MCP config.
Generate a config snippet (defaults to test_mcp_key; add --env PEARCH_API_KEY=your-key for full results):
fastmcp install mcp-json pearch_mcp.py --name "Pearch.ai"
Paste the generated object into your client’s mcpServers.
Tools
| Tool | Description |
|---|---|
| search_people | Natural-language search for people or follow-up on a thread. Example: "software engineers in California with 5+ years Python", "senior ML researchers in Berlin". |
| search_company_leads | Find companies and leads/contacts (B2B). Example: company "AI startups in SF, 50–200 employees" + leads "CTOs and engineering managers". |
Base URL: PEARCH_API_URL or per-call base_url (default https://api.pearch.ai).
Development
export PEARCH_API_KEY='test_mcp_key' # or your key for full results
fastmcp dev inspector pearch_mcp.py
Support
License
MIT — see LICENSE.
관련 서버
Amadeus MCP Server
Search for flight offers using the Amadeus Flight Offers Search API.
Ollama Deep Researcher
Conducts deep research using local Ollama LLMs, leveraging Tavily and Perplexity for comprehensive search capabilities.
IMDb MCP Server
Provides movie and TV show information using the IMDb API service.
Google Maps MCP Server
Local business search and lead generation via Google Maps
Sci-Hub MCP Server
Search and access academic papers from Sci-Hub by DOI, title, or keyword.
Web Search
Perform Google searches and view web content with advanced bot detection avoidance.
AI Book Agent MCP Server
Provides AI assistants with intelligent access to ML textbook content for creating accurate, source-grounded documentation.
Kagi
Kagi search API integration
LeadMagic
Access LeadMagic's B2B data enrichment API suite for email finding, profile enrichment, and company intelligence.
Custom Elasticsearch
A simple MCP server for Elasticsearch, designed for cloud environments where your public key is already authorized.