http-client-mcp

keijeizei/http-client-mcp

3.2

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A Model Context Protocol (MCP) server that provides HTTP client capabilities.

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HTTP Client MCP Server

A Model Context Protocol (MCP) server that provides HTTP client capabilities.

Features

  • Full HTTP method support (GET, POST, PUT, DELETE, PATCH, HEAD, OPTIONS)
  • Custom headers and query parameters
  • Request body support (JSON, form data, text)
  • Configurable timeouts and SSL verification
  • Detailed response information including status codes and headers

Setup for Claude Desktop

1. Install Dependencies

pip install fastmcp httpx pydantic

Or use the requirements file:

pip install -r requirements.txt

2. Configure Claude Desktop

Add this server to your Claude Desktop configuration file:

Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "http-client": {
      "command": "python",
      "args": ["/path/to/http-client-mcp/src/http_client_mcp/server.py"]
    }
  }
}

Note: Replace /path/to/http-client-mcp with the actual location where you cloned this repository.

3. Restart Claude Desktop

After saving the configuration, restart Claude Desktop to load the MCP server.

Usage Examples

Once configured, you can use these tools:

Simple GET request:

Use the http_get tool to fetch data from https://api.github.com/users/octocat

POST request with JSON:

Use the http_post tool to send {"name": "test"} to https://httpbin.org/post

Custom request:

Use the http_request tool to make a PUT request to https://httpbin.org/put with custom headers

Available Tools

  • http_request - Full control over HTTP requests
  • http_get - Simplified GET requests
  • http_post - Simplified POST requests
  • http_put - Simplified PUT requests
  • http_delete - Simplified DELETE requests
  • http_patch - Simplified PATCH requests

License

MIT License - see file for details.

AI-Assisted Development

This repository was created with the assistance of AI tools. The time invested in building a solution should not exceed the time it saves compared to not building it at all.