Tracxn MCP Server

Name: Tracxn MCP Server
Author: vatsal191201

@vatsal191201

代码仓库

关于 Tracxn MCP Server

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

#tracxn #mcp #api-server

基本信息

分类

其他

许可证

MIT license

运行时

python

传输方式

stdio

发布者

vatsal191201

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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.

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