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The Cutshort MCP (Model Context Protocol) server lets you integrate Cutshort’s hiring capabilities into AI agents, LLM-powered assistants, and tools like Claude Desktop and Cursor. Instead of building custom API glue, you configure the MCP server once and your AI agent can search candidates, post jobs, and generate shortlists as natural tool calls.

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What MCP enables

AI Hiring Assistant

Let Claude or GPT-4 search candidates and answer hiring queries

Automated Sourcing

Build agents that run end-to-end sourcing without code

Slack/Teams Bots

Create HR bots that answer “who should we interview?” in real time

Custom Agents

Integrate Cutshort tools into any MCP-compatible AI framework

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How it works

The Cutshort MCP server sits between your AI agent and the Cutshort platform, translating natural-language tool calls into structured API requests:
  1. Your AI agent (Claude, GPT-4, etc.) is connected to the Cutshort MCP server.
  2. The agent calls Cutshort tools (search_candidates, create_job, etc.) using natural language.
  3. The MCP server translates the call to a Cutshort API request and returns results.
  4. The agent uses the results to answer questions or take further actions.

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Available tools

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REST API vs MCP

The REST API is best for custom integrations, ATS sync, job board tools, and scheduled data pulls. You write the integration code — defining endpoints, handling authentication, parsing responses, and managing retries. Choose the REST API when you need precise control over request structure or want to embed Cutshort data in your own backend pipelines.
The MCP server uses your Cutshort API key for authentication — the same key you use for REST API calls.