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Tracxn MCP Server

@vatsal191201

代码仓库

基本信息

分类

其他

许可证

MIT license

传输方式

stdio

作者

vatsal191201

关于 Tracxn MCP Server

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

#tracxn#mcp#api-server

Tracxn MCP Server 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"
      ]
    }
  }
}

Tracxn MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

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

常见问题

1

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`).

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.

3

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.

4

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).

5

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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