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Tracxn MCP Server: Future-Proof Analytics & Seamless API Automation - MCP Implementation

Tracxn MCP Server: Future-Proof Analytics & Seamless API Automation

Tracxn MCP Server: The go-to Model Control Protocol for seamless API integration, automating data workflows and future-proofing your analytics game.

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About Tracxn MCP Server

What is Tracxn MCP Server: Future-Proof Analytics & Seamless API Automation?

Tracxn MCP Server is a specialized API gateway designed to enable AI models and developers to access Tracxn’s extensive database of company profiles, investment transactions, and market trends. This server acts as an intermediary, simplifying interaction with Tracxn’s API while ensuring scalability and stability for automated workflows. Currently in active development, it prioritizes future compatibility with emerging analytics tools and machine learning frameworks.

How to Use Tracxn MCP Server: Future-Proof Analytics & Seamless API Automation?

  1. Setup: Clone the repository and install dependencies using pip install -r requirements.txt.
  2. Configuration: Set your Tracxn API token via environment variables (TRACXN_API_KEY).
  3. Execution: Launch the server with python main.py, then integrate endpoints into your analytics pipelines.

Pro Tip: Use the --debug flag during testing to log detailed API interactions.

Tracxn MCP Server Features

Key Features of Tracxn MCP Server: Future-Proof Analytics & Seamless API Automation?

  • Data Aggregation: Unify real-time company metrics, investment histories, and market sentiment into a single API layer.
  • Rate Limit Management: Built-in throttling ensures compliance with API quotas without manual intervention.
  • Schema Flexibility: Output formats dynamically adapt to JSON, CSV, or custom schemas via query parameters.
  • Batch Processing: Process large datasets incrementally with pagination and checkpointing.

Use Cases of Tracxn MCP Server: Future-Proof Analytics & Seamless API Automation?

  • Portfolio Optimization: Automate risk assessment by cross-referencing investment trends with company performance data.
  • Competitor Analysis: Track industry leaders’ funding rounds and patent activity through continuous API polling.
  • Regulatory Reporting: Generate compliance-ready reports using predefined templates and audit logs.
  • AI Training Data: Curate labeled datasets for training models on startup valuations or exit outcomes.

Tracxn MCP Server FAQ

FAQ from Tracxn MCP Server: Future-Proof Analytics & Seamless API Automation?

How do I handle API rate limits?
The server automatically queues requests and retries failed calls. Monitor the /status endpoint for quota usage.
Can I customize data fields?
Yes—add fields=parameter1,parameter2 to API requests to return only relevant data points.
What authentication methods are supported?
Token-based authentication via header. OAuth2 support is planned for the next release.
Where can I find API documentation?
Run python main.py docs to generate Swagger-compliant documentation locally.

Content

Tracxn MCP Server

A Model Control Protocol (MCP) server implementation for interacting with the Tracxn API. This server enables AI models to access Tracxn's comprehensive database of companies, investors, transactions, and market intelligence.

🚧 Work in Progress

This project is currently under active development. Some features may be incomplete or subject to change.

Features

Company Information

  • Search companies by sector, name, or domain
  • Filter by funding amounts, location, founding year
  • Detailed company profiles including business models and funding history

Investment Data

  • Search funding transactions and rounds
  • Filter by date, amount, round type
  • Investor details and portfolio information

Market Intelligence

  • Practice area insights
  • Business model categorization
  • Industry feeds and sectors

Requirements

  • Python 3.8 or higher
  • Tracxn API access token

Installation

  1. Clone the repository:
git clone 
cd tracxn-mcp
  1. Install dependencies:
pip install -r requirements.txt
  1. Set your Tracxn API token:
# On macOS/Linux

export TRACXN_ACCESS_TOKEN = "your-token-here"


# On Windows Command Prompt

set TRACXN_ACCESS_TOKEN = your-token-here


# On Windows PowerShell

$env:TRACXN_ACCESS_TOKEN="your-token-here"

Usage

Run the server:

python tracxn_server.py

Tools Available

1.search_companies: Search companies with various filters

2.company_lookup: Get detailed information about a specific company

3.funded_companies: Find companies within specific funding ranges

4.search_companies_by_name: Search companies by their name

5.search_transactions: Find funding rounds and transactions

6.search_investors: Search for investors and their portfolios

7.search_acquisitions: Find acquisition deals

8.search_practice_areas: Explore practice areas

9.search_feeds: Access industry feeds

10.search_business_models: Find business model categories

11.debug_api_call: Debug API requests

12.diagnose_api_request: Diagnose API request format issues

API Endpoints

The server uses Tracxn's API v2.2 with both playground and production environments:

  • Playground: https://platform.tracxn.com/api/2.2/playground
  • Production: https://platform.tracxn.com/api/2.2

Known Issues and Limitations

  • Maximum of 20 results per request
  • Some sectors may require specific access permissions
  • Rate limiting applies to API calls
  • Sort fields must be specified in certain formats
  • The following errors may occur:
  • Sort field errors: Some endpoints require specific sort field formats
  • Domain format issues: Company lookup may need domain as a list or string
  • Invalid sector access: Some sectors may not be accessible depending on API permissions

Error Handling

The server handles various API response codes:

  • 200: Success
  • 400: Bad Request
  • 401: Authentication Issue
  • 403: Unauthorized/Credit Limit Exceeded
  • 404: Not Found
  • 429: Rate Limit Exceeded
  • 500: Internal Server Error

Development

Project Structure

-tracxn_server.py: Main server implementation

-requirements.txt: Python dependencies

-README.md: Project documentation

Debugging

Use the debug_api_call and diagnose_api_request tools to troubleshoot API issues.

Contributing

This is a work in progress, and contributions are welcome. Please ensure you test your changes thoroughly before submitting pull requests.

Support

For API-related issues, contact Tracxn support at [email protected]


Note : This implementation is still under development. Features and functionality may change as we continue to improve the integration with Tracxn's API.

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