Mcp Agent Kit

Name: Mcp Agent Kit
Author: dominiquekossi

@dominiquekossi

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

基本信息

分类

AI 与智能体

传输方式

stdio

发布者

dominiquekossi

提交者

dom s

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"
      }
    }
  }
}

工具

未检测到工具

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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

FAQ from Mcp Agent Kit

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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