MCP Pearch

مجتمعي البحث والويب

People search engine for talent discovery.

التثبيت

خطوات التثبيت موجودة في التوثيق أدناه. التوثيق

التوثيق

مأخوذ من ملف README للمشروع على GitHub ويُحدَّث أسبوعيًا. تفتح الروابط على GitHub.

المحتويات
  1. Pearch.ai MCP
  2. Tools
  3. Remote server (recommended)
  4. Local (stdio) installation
  5. Running your own HTTP server
  6. Development
  7. Privacy Policy
  8. Support
  9. License

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

ToolDescription
search_peoplePeople search with a natural-language query or structured search_requirements. Supports fast/pro/superfast search types, contact reveal & contact filters, real-time profile refresh, insights, and thread-based pagination/follow-ups.
search_company_leadsFind 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_profileLook up and enrich a single person by LinkedIn slug or email (contact reveal, real-time refresh, GitHub enrichment).
get_user_infoAuthenticated user info: email, remaining credits, pricing plan. Free.

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: true for mandatory criteria, false for 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.

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/mcp

Your 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_key

Or 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_key

Replace 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 8000

Health: GET /health or /healthcheck (reports the auth mode).

Environment variables
VariableDefaultPurpose
PEARCH_MCP_AUTHapi_keyoauth \api_key \none. In oauth mode raw API-key bearers are still accepted (dual auth).
PEARCH_MCP_BASE_URLhttp://localhost:8000Public URL of this server. OAuth metadata, token audience, and the /auth/callback redirect URI all derive from it.
PEARCH_MCP_GOOGLE_CLIENT_ID / PEARCH_MCP_GOOGLE_CLIENT_SECRET—Google OAuth 2.0 Web application client (register <base_url>/auth/callback as a redirect URI). Required in oauth mode.
PEARCH_MCP_INTERNAL_TOKEN—Shared secret for internal email→API-key mapping and request-source signing. Required in oauth mode and for verified MCP attribution with API keys. Must match the backend's MCP_INTERNAL_TOKEN; never distribute to end users.
PEARCH_MCP_OAUTH_STOREdiskredis keeps OAuth state (client registrations, tokens — encrypted) in Redis so it survives restarts and allows >1 replica.
PEARCH_MCP_OAUTH_REDIS_HOST / REDIS_ENDPOINT, REDIS_PORT, PEARCH_MCP_OAUTH_REDIS_DB, REDIS_PASSWORD—, 6379, 4, —Redis connection for the OAuth store.
PEARCH_MCP_ALLOWED_CLIENT_REDIRECT_URISbuilt-in listComma-separated fnmatch patterns for MCP client redirect URIs (* = any).
PEARCH_MCP_TOKEN_CACHE_TTL_S300Verified-identity cache TTL; also the revocation lag.
PEARCH_API_URLhttps://api.pearch.aiPearch API base (per-call base_url overrides).
PEARCH_API_KEYtest_mcp_keyFallback key for stdio/local use.
MCP_DISABLE_AUTH—1 is equivalent to PEARCH_MCP_AUTH=none (local dev only).

Tool requests to the Pearch API include X-Pearch-Source: mcp on both POST and GET calls, including people search, company-leads search, pagination, and profile enrichment. The hosted server also sends X-Pearch-Source-Signature when the internal secret is configured and the destination origin matches PEARCH_API_URL. The HMAC binds the bearer credential, method, decoded path plus raw query, body, and timestamp. The backend accepts signatures within 300 seconds, so server clocks must be synchronized. Caller-supplied base_url values on other origins receive no signature.

The backend records verified MCP traffic as api_calls.request_source for analytics and DevAdmin history. A bare source header is insufficient. Unsigned self-hosted MCP traffic using API keys remains api; authenticated allowlisted OAuth clients are recognized without headers. Deploy signing before enabling backend source logging, after applying its database migration. Older backends ignore the headers. Authentication, account attribution, and billing are unchanged.

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.py

Privacy 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.

الأسئلة الشائعة

ما هو MCP Pearch؟

People search engine for talent discovery.

كيف أثبّت MCP Pearch؟

اتبع خطوات التثبيت في توثيقه المعروض في هذه الصفحة وفي مستودعه.

هل MCP Pearch مفتوح المصدر؟

نعم. شيفرته متاحة على GitHub بترخيص MIT.

من يصون MCP Pearch؟

ينشره Pearch-ai. يدرجه AI.tn لكنه لا يصونه ولا يوصي به.

من القوائم المجتمعية awesome-mcp-servers ومستودع المشروع على GitHub. الإدراج ليس توصية: راجع شيفرة الخادم وصلاحياته قبل منحه الوصول إلى بياناتك.