Pearch.ai MCP

Pearch.ai MCP

Natural Language People Search and Candidate Sourcing API for Seamless ATS Integration

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Pearch.ai MCP provides a high-precision people search API that interprets natural language queries to deliver top-quality candidate results. Designed for easy integration with Applicant Tracking Systems and hiring platforms, it leverages scientific methods and is trusted by recruiters. The tool is implemented as a Model Context Protocol (MCP), facilitating standardized model context handling and deployment via packages like FastMCP or through Smithery. The solution prioritizes ease of use, reliability, and high candidate match accuracy.

Key Features

Natural language query interpretation
High-precision candidate ranking
API key authentication support
Standardized MCP/fastmcp integration
Seamless ATS compatibility
Cross-platform installation (macOS, Linux, Smithery)
Local development and testing support
MIT License for open use
Environment variable configuration
Validated by recruiter and scientific evaluation

Use Cases

Integrating high-quality people search into recruiting platforms
Enhancing applicant tracking systems with natural language search capabilities
Automating candidate sourcing for in-house HR teams
Enabling third-party hiring platforms to deliver better candidate matches
Supporting AI-powered sourcing assistants
Boosting recruiter productivity through precise recommendations
Configuring local dev/test environments for candidate search APIs
Implementing scientific, evidence-based recruitment tools
Enterprise integrations needing robust, standardized model context handling
Rapid deployment of sourcing tools via package managers

README

Pearch.ai MCP

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Our 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.

Evaluating AI Recruitment Sourcing Tools by Human Preference

Prerequisites

  • Python 3.7 or newer
  • Pearch.ai API key
  • FastMCP package

API Key Setup

  1. Visit Pearch.ai Dashboard to obtain your API key
  2. Set your API key as an environment variable:
    bash
    export PEARCH_API_KEY='your-api-key-here'
    

Installation

Installing via Smithery

To install mcp_pearch for Claude Desktop automatically via Smithery:

bash
npx -y @smithery/cli install @Pearch-ai/mcp_pearch --client claude

Option 1: macOS[uv]

bash
# Install Python and uv
brew install python
brew install uv

# Create and activate virtual environment
uv venv
source .venv/bin/activate

# Install FastMCP
uv pip install fastmcp

Option 2: Linux[pip]

bash
# Install system dependencies
sudo apt update
sudo apt install python3 python3-venv python3-pip

# Create and activate virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install FastMCP
pip install fastmcp

Usage

Standard Installation

bash
fastmcp install pearch_mcp.py --name "Pearch.ai" --env-var PEARCH_API_KEY=pearch_mcp_key

Development Mode

For local development and testing:

bash
# Set your API key
export PEARCH_API_KEY='your-api-key-here'

# Start development server
fastmcp dev pearch_mcp.py

Support

If you encounter any issues or have questions:

  • Open an issue in the repository
  • Contact support at f@pearch.ai

License

This project is licensed under the MIT License - see the LICENSE file for details.

Star History

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Repository Owner

Pearch-ai
Pearch-ai

Organization

Repository Details

Language Python
Default Branch main
Size 15 KB
Contributors 2
License MIT License
MCP Verified Nov 12, 2025

Programming Languages

Python
73.93%
Dockerfile
26.07%

Tags

Topics

ai api human-resources mcp

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