MCP Agent Kit

@dominiquekossi

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

dominiquekossi

提交者

dom s

关于 MCP Agent Kit

a complete and intuitive SDK for building MCP Servers, MCP Agents, and LLM integrations (OpenAI, Claude, Gemini) with minimal effort.

#mcp-agent-kit#sdk #ai-agents

MCP Agent Kit 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-agent-kit": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-agent-kit"
      ],
      "env": {
        "MCP_SERVER_NAME": "my-server",
        "MCP_PORT": "7777",
        "LOG_LEVEL": "info",
        "OPENAI_API_KEY": "sk-...",
        "ANTHROPIC_API_KEY": "sk-ant-...",
        "GEMINI_API_KEY": "...",
        "OLLAMA_HOST": "http://localhost:11434"
      }
    }
  }
}

MCP Agent Kit 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。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is Mcp Agent Kit?

Mcp Agent Kit is a TypeScript package that simplifies creating MCP (Model Context Protocol) servers, AI agents, intelligent LLM routers, chatbots with conversation memory, and HTTP API helpers with built-in retry and timeout. It supports multiple LLM providers and is designed for developers who want to quickly build production-ready agents and tools.

How to use Mcp Agent Kit?

Install the package via npm (npm install mcp-agent-kit), then use functions like createAgent, createMCPServer, createChatbot, and createLLMRouter to build components. Configuration is optional via environment variables or code parameters. Examples are available in the /examples directory and can be run with npx ts-node.

Key features of Mcp Agent Kit

Zero config with smart defaults
Multi-LLM provider support (OpenAI, Anthropic, Gemini, Ollama)
Full TypeScript support and autocomplete
Built-in retry, timeout, and error handling
One-line setup for complex features (agents, servers, chatbots)
Extensible with custom providers and middleware

Use cases of Mcp Agent Kit

Create an MCP server to expose tools and resources to clients
Build an AI agent with function calling and system prompts
Develop a chatbot with automatic conversation memory and history limits
Route requests to different LLMs based on input length or content rules
Simplify HTTP requests with automatic retry and configurable timeout

常见问题

Which LLM providers are supported?

OpenAI, Anthropic, Gemini, and Ollama are supported out of the box.

Do I need API keys for all providers?

API keys are required for OpenAI, Anthropic, and Gemini. Ollama runs locally and does not need an API key.

Can I use WebSocket transport for MCP servers?

Yes – call `server.start("websocket")` to start the server on WebSocket instead of stdio.

How do I configure environment variables?

Set variables like `OPENAI_API_KEY` or `LOG_LEVEL` in a `.env` file or in your environment. The package automatically loads `.env` files using dotenv.

What is the default transport for MCP servers?

The default transport is stdio, unless you specify `"websocket"` as an argument to `start()`.

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