Pearch
OfficialSupports deployment on Linux systems, enabling Linux users to integrate Pearch.ai's people search capabilities into their applications.
Provides installation support for macOS environments, allowing macOS users to deploy the people search functionality on Apple's operating system.
Enables integration with Python applications, allowing developers to embed Pearch.ai's powerful people search capabilities within Python-based software.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Pearchfind senior Python developers with AWS experience in San Francisco"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Pearch.ai MCP
MCP server for Pearch.AI: natural-language search over people and companies/leads (B2B). Use it from Claude, Cursor, VS Code, or any MCP-compatible client.
Evaluating AI Recruitment Sourcing Tools by Human Preference
Tools
Tool | Description |
search_people | People search with a natural-language |
search_company_leads | Find companies and leads/contacts within them (B2B). Example: company "AI startups in SF, 50–200 employees" + leads "CTOs and engineering managers", with optional personalized outreach messages. |
get_profile | Look up and enrich a single person by LinkedIn slug or email (contact reveal, real-time refresh, GitHub enrichment). |
get_user_info | Authenticated user info: email, remaining credits, pricing plan. Free. |
Structured people search
Pass search_requirements to search_people when you already have a list of criteria:
{
"search_requirements": [
{
"search_requirement": "Software engineer with 5+ years of Python experience",
"must_have": true
},
{
"search_requirement": "Experience at a fintech company",
"must_have": false
}
],
"search_type": "fast",
"limit": 10,
"insights": true,
"reveal_emails": true
}search_requirement: required, non-empty text. Keep each criterion short and self-contained.must_have:truefor mandatory criteria,falsefor nice-to-have preferences (the default).
The list must contain at least one requirement. query is optional when using
search_requirements; if both are supplied, the API gives search_requirements
precedence. See the Pearch search API contract.
Both inputs support the same search options: search type, insights and scoring,
profile refresh, contact reveal and filters, strict filtering, low-confidence
results, time budget, pagination, response fields, profile exclusions, and free
masked results. Search-type restrictions are the same for both inputs; for example,
superfast does not support insights, profile scoring, or high freshness.
For pagination, send the returned thread_id with limit and optionally offset,
omitting query and search_requirements. To change criteria, start a new search
without thread_id. Existing query calls and thread follow-ups are still forwarded
as before; the API decides which follow-up parameters it accepts.
custom_filters is not exposed by this MCP server. Express criteria in query or
search_requirements instead.
Related MCP server: Potarix enricher
Remote server (recommended)
The hosted server lives at https://mcp.pearch.ai/mcp and supports two auth schemes at once:
OAuth (no key handling)
Add the server without any headers — OAuth-capable clients (Claude, Cursor, VS Code) discover the flow automatically and open a Google sign-in. Sign in with the Google account whose email matches your Pearch account:
claude mcp add --transport http pearch https://mcp.pearch.ai/mcpYour searches bill credits against your own Pearch account. If your Pearch account has no API key yet, create one first in the Pearch.ai Dashboard.
API key
Pass the same Pearch API key as api.pearch.ai:
{
"mcpServers": {
"Pearch.ai": {
"url": "https://mcp.pearch.ai/mcp",
"headers": {
"Authorization": "Bearer ${env:PEARCH_API_KEY}"
}
}
}
}Use test_mcp_key for masked (sample) results — no sign-up required.
Local (stdio) installation
Requires Python 3.10+ and pip install -r requirements.txt (or pip install fastmcp).
Claude Desktop / Claude Code
fastmcp install claude-desktop pearch_mcp.py --env PEARCH_API_KEY=test_mcp_keyOr manually under mcpServers:
"Pearch.ai": {
"command": "python",
"args": ["/path/to/mcp_pearch/pearch_mcp.py"],
"env": { "PEARCH_API_KEY": "test_mcp_key" }
}Cursor
fastmcp install cursor pearch_mcp.py --env PEARCH_API_KEY=test_mcp_keyReplace test_mcp_key with your dashboard key for full results.
Running your own HTTP server
uvicorn pearch_mcp:app --host 0.0.0.0 --port 8000Health: GET /health or /healthcheck (reports the auth mode).
Environment variables
Variable | Default | Purpose |
|
|
|
|
| Public URL of this server. OAuth metadata, token audience, and the |
| — | Google OAuth 2.0 Web application client (register |
| — | Shared secret for the Pearch API's internal email→API-key mapping endpoint. Required in |
|
|
|
| —, | Redis connection for the OAuth store. |
| built-in list | Comma-separated fnmatch patterns for MCP client redirect URIs ( |
|
| Verified-identity cache TTL; also the revocation lag. |
|
| Pearch API base (per-call |
|
| Fallback key for stdio/local use. |
| — |
|
In oauth mode the ingress/reverse proxy must route the whole host to the server, not just /mcp: the flow adds /.well-known/oauth-*, /authorize, /token, /register, /revoke, /consent, and /auth/callback.
Development
export PEARCH_API_KEY='test_mcp_key' # or your key for full results
fastmcp dev inspector pearch_mcp.pyPrivacy Policy
Pearch.AI's privacy policy: https://pearch.ai/privacy-policy — covers data collection, usage, storage, third-party sharing, retention, and contact information. Data deletion / opt-out: https://pearch.ai/opt-out. Terms of service: https://pearch.ai/tos.
Support
License
MIT — see LICENSE.
This server cannot be deployed
Maintenance
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