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Tracxn MCP Server

@vatsal191201

Repository

About Tracxn MCP Server

A Model Control Protocol (MCP) server implementation for interacting with the Tracxn API

#tracxn#mcp#api-server

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "tracxn-mcp": {
      "command": "python",
      "args": [
        "tracxn_server.py"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Tracxn MCP Server?

Tracxn MCP Server is a Model Context Protocol (MCP) server implementation that enables AI models to access the Tracxn API, providing comprehensive data on companies, investors, funding transactions, and market intelligence.

How to use Tracxn MCP Server?

Install Python dependencies (Python 3.8+ required), set the TRACXN_ACCESS_TOKEN environment variable with your Tracxn API token, and run python tracxn_server.py. The server exposes tools such as search_companies, company_lookup, search_transactions, search_investors, and search_acquisitions for querying Tracxn data.

Key features of Tracxn MCP Server

  • Search companies by sector, name, or domain
  • Filter by funding amounts, location, and founding year
  • Detailed company profiles with funding history
  • Search funding rounds and transactions
  • Explore practice areas, business models, and industry feeds
  • Debug and diagnose API requests

Use cases of Tracxn MCP Server

  • AI agents performing company and investor research
  • Automated market intelligence and sector analysis
  • Finding companies within specific funding ranges
  • Searching for recent funding rounds and acquisition deals
  • Exploring industry feeds and business model categories

FAQ from Tracxn MCP Server

What data sources does Tracxn MCP Server connect to?

It connects to the Tracxn API v2.2, using either the playground environment (https://platform.tracxn.com/api/2.2/playground) or the production environment (https://platform.tracxn.com/api/2.2).

What are the runtime requirements?

Python 3.8 or higher and a valid Tracxn API access token set as the TRACXN_ACCESS_TOKEN environment variable.

What limits does the server have?

Maximum of 20 results per request; rate limiting applies to API calls; some sectors require specific access permissions; sort fields must be formatted correctly.

How are API errors handled?

The server maps HTTP status codes: 200 (Success), 400 (Bad Request), 401 (Authentication Issue), 403 (Unauthorized/Credit Limit Exceeded), 404 (Not Found), 429 (Rate Limit Exceeded), and 500 (Internal Server Error).

How can I debug API issues?

Use the built-in debug_api_call and diagnose_api_request tools to troubleshoot API request formatting and response issues.

Frequently asked questions

What data sources does Tracxn MCP Server connect to?

It connects to the Tracxn API v2.2, using either the playground environment (`https://platform.tracxn.com/api/2.2/playground`) or the production environment (`https://platform.tracxn.com/api/2.2`).

What are the runtime requirements?

Python 3.8 or higher and a valid Tracxn API access token set as the `TRACXN_ACCESS_TOKEN` environment variable.

What limits does the server have?

Maximum of 20 results per request; rate limiting applies to API calls; some sectors require specific access permissions; sort fields must be formatted correctly.

How are API errors handled?

The server maps HTTP status codes: 200 (Success), 400 (Bad Request), 401 (Authentication Issue), 403 (Unauthorized/Credit Limit Exceeded), 404 (Not Found), 429 (Rate Limit Exceeded), and 500 (Internal Server Error).

How can I debug API issues?

Use the built-in `debug_api_call` and `diagnose_api_request` tools to troubleshoot API request formatting and response issues.

Comments

Basic information

Category

Other

License

MIT license

Transports

stdio

Author

vatsal191201

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