{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_6fq66d8nup73","handle":"iflow-mcp-mcp-pearch","url":"https://wellknown.network/agents/iflow-mcp-mcp-pearch","links":{"self":"https://wellknown.network/agents/iflow-mcp-mcp-pearch/record.json","html":"https://wellknown.network/agents/iflow-mcp-mcp-pearch","markdown":"https://wellknown.network/agents/iflow-mcp-mcp-pearch/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-pearch","status":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-pearch/status","claim":"https://wellknown.network/agents/iflow-mcp-mcp-pearch/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-mcp-pearch/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-mcp-pearch/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-pearch/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-mcp-pearch/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-mcp-pearch","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_mcp_pearch","summary":"The most accurate people search API/MCP. Natural language in, high-quality candidates out. Built for ATSs and AI Agents.","description":"# Pearch.ai MCP\n\n[![smithery badge](https://smithery.ai/badge/@Pearch-ai/mcp_pearch)](https://smithery.ai/server/@Pearch-ai/mcp_pearch)\n\nOur people search API and MCP deliver the most precise results on the market. You simply ask in natural language, and we provide top-quality candidates. Designed for seamless integration with any ATS or hiring platform, our solution is backed by scientific methods, trusted by recruiters, and consistently rated the highest-quality sourcing tool.\n\n[Evaluating AI Recruitment Sourcing Tools by Human Preference](https://arxiv.org/abs/2504.02463v1)\n\n## Prerequisites\n\n- Python 3.7 or newer\n- Pearch.ai API key\n- FastMCP package\n\n## API Key Setup\n\n1. Visit [Pearch.ai Dashboard](https://platform.pearch.ai/dashboard) to obtain your API key\n2. Set your API key as an environment variable:\n   ```bash\n   export PEARCH_API_KEY='your-api-key-here'\n   ```\n\n## Installation\n\n### Installing via Smithery\n\nTo install mcp_pearch for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@Pearch-ai/mcp_pearch):\n\n```bash\nnpx -y @smithery/cli install @Pearch-ai/mcp_pearch --client claude\n```\n\n### Option 1: macOS[uv] \n\n```bash\n# Install Python and uv\nbrew install python\nbrew install uv\n\n# Create and activate virtual environment\nuv venv\nsource .venv/bin/activate\n\n# Install FastMCP\nuv pip install fastmcp\n```\n\n### Option 2: Linux[pip] \n\n```bash\n# Install system dependencies\nsudo apt update\nsudo apt install python3 python3-venv python3-pip\n\n# Create and activate virtual environment\npython3 -m venv .venv\nsource .venv/bin/activate\n\n# Install FastMCP\npip install fastmcp\n```\n\n## Usage\n\n### Standard Installation\n\n```bash\nfastmcp install pearch_mcp.py --name \"Pearch.ai\" --env-var PEARCH_API_KEY=pearch_mcp_key\n```\n\n### Development Mode\n\nFor local development and testing:\n\n```bash\n# Set your API key\nexport PEARCH_API_KEY='your-api-key-here'\n\n# Start development server\nfastmcp dev pearch_mcp.py\n```\n\n## Support\n\nIf you encounter any issues or have question…","publisher":null,"homepage":null,"repository":null,"version":"1.0.0","license":"MIT","protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_mcp_pearch","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","summary":"pypi","version":"pypi","description":"pypi"}},"derived":{"capabilities":[{"slug":"productivity.hr","name":"HR & Recruiting","confidence":1,"provenance":"derived"},{"slug":"dev.package-management","name":"Packages & Dependencies","confidence":0.859,"provenance":"derived"},{"slug":"research.academic","name":"Academic Research","confidence":0.814,"provenance":"derived"}],"categories":["dev","productivity","research"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_mcp_pearch","registry":"pypi","observedAt":"2026-11-03T07:26:01.288Z","publishedAt":"2025-11-28T06:24:55.071003Z","latestVersion":"1.0.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_mcp_pearch","url":"https://pypi.org/project/iflow-mcp_mcp_pearch/","firstSeenAt":"2026-09-09T20:23:34.430Z","fetchedAt":"2026-11-03T07:25:03.407Z","normalizedAt":"2026-11-03T07:25:03.407Z"}]},"firstSeenAt":"2026-09-09T20:23:34.430Z","updatedAt":"2026-11-03T07:26:01.288Z"}