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πŸš€ MCP-AI: Self-Learning API-to-cURL Model

@S-Umasankar

About πŸš€ MCP-AI: Self-Learning API-to-cURL Model

No overview available yet

Basic information

Category

Developer Tools

Runtime

python

Transports

stdio

Publisher

S-Umasankar

Config

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

{
  "mcpServers": {
    "api-to-curl-mcp-server": {
      "command": "python",
      "args": [
        "src/ai_autonomous_dev.py"
      ]
    }
  }
}

Tools

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Overview

What is πŸš€ MCP-AI: Self-Learning API-to-cURL Model?

This project builds an autonomous AI system that converts API documentation into cURL commands. It uses reinforcement learning to self-improve and is deployed via an MCP server with continuous integration through GitHub Actions.

How to use πŸš€ MCP-AI: Self-Learning API-to-cURL Model?

Install dependencies with pip install -r requirements.txt, then start the MCP server by running bash scripts/start_mcp.sh. Launch the AI automation with python src/ai_autonomous_dev.py, and test the system with pytest tests/.

Key features of πŸš€ MCP-AI: Self-Learning API-to-cURL Model

  • Automated dataset generation from API documentation
  • Self-improving model with reinforcement learning
  • MCP server for API-based execution
  • Continuous deployment with GitHub Actions
  • Packaged as an SDK via setup.py
  • Includes pre- and post-training scripts (pre_train.py, post_train.py)

Use cases of πŸš€ MCP-AI: Self-Learning API-to-cURL Model

  • Automatically generating cURL commands from any REST API documentation
  • Rapid prototyping and testing of API endpoints
  • Training and deploying a dedicated AI model for API-to-cURL conversion
  • Integrating cURL generation into CI/CD pipelines via the MCP server

FAQ from πŸš€ MCP-AI: Self-Learning API-to-cURL Model

What are the main dependencies?

The setup.py requires FastAPI, Uvicorn, PyTorch, Transformers, sacrebleu, requests, pytest, and GitPython.

How do I start the MCP server?

Run bash scripts/start_mcp.sh. If uvicorn is not found, ensure it is installed (pip install uvicorn) and activate the Python virtual environment. Alternatively, modify the script to call python -m uvicorn.

How can I test the system?

Use pytest tests/ after installing dependencies and starting the server.

What is the role of the MCP server?

It provides an API-based interface to execute the cURL generation model, enabling integration with other tools and workflows.

Does the server require authentication or configure a specific transport?

The README does not mention any authentication mechanism or transport configuration beyond the default Uvicorn HTTP server.

Comments

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