Model Context Protocol (MCP) Server

Name: Model Context Protocol (MCP) Server
Author: shaswata-das

@shaswata-das

代码仓库

关于 Model Context Protocol (MCP) Server

暂无概览

#mcp-server #ai-services #json-rpc

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

shaswata-das

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "basic-mcp-server-shaswata-das": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

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 Model Context Protocol (MCP) Server?

A modular Model Context Protocol server for AI services that supports multiple AI providers (Claude, OpenAI, and a mock service) and transport options (stdio, TCP, and WebSocket). It provides a JSON‑RPC 2.0 interface for tool calling and resource management, with dynamic service selection on a per‑request basis.

How to use Model Context Protocol (MCP) Server?

Clone the repository, create a virtual environment, install dependencies with pip install -e ., and configure API keys via the .env file. Run the server with python mcp_server.py (defaults to stdio mode) or use --tcp or --websocket flags to choose other transports. Interact using the provided example clients (examples/example_client.py and examples/websocket_client.html).

Key features of Model Context Protocol (MCP) Server

Multiple AI services (Claude, OpenAI, mock) selectable per request
Three transport options: stdio, TCP, and WebSocket
JSON‑RPC 2.0 compliant interface for predictable interactions
Dynamic service selection without restarting the server
Streaming response support for compatible transports
Modular architecture for easy extension with new services and transports
Qdrant vector database integration for embeddings and semantic search

Use cases of Model Context Protocol (MCP) Server

Build AI‑powered command‑line tools that can switch between models at runtime
Integrate AI assistants into web browsers using WebSocket transport
Test and develop AI workflows locally with the mock service, then swap in real APIs
Deploy a single server that serves multiple AI backends behind a load balancer

FAQ from Model Context Protocol (MCP) Server

What AI services are supported?

The server supports Claude

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