OpenAI MCP Server

# Claude Code MCP Examples This directory contains examples for using the Claude Code MCP client with different MCP servers. ## Echo Server A simple server that provides two tools: - `echo`: Echoes back any message sent to it - `reverse`: Reverses any message sent to it To run the echo server example: 1. Start the server: ```bash python examples/echo_server.py ``` 2. In a separate terminal, connect to it with the MCP client: ```bash claude mcp-client examples/echo_server.py ``` 3. Try these example queries: - "Echo the phrase 'hello world'" - "Can you reverse the text 'Claude is awesome'?" ## Multi-Agent Example The `agents_config.json` file contains a configuration for a multi-agent setup with three specialized roles: - **Researcher**: Focuses on finding and analyzing information - **Coder**: Specializes in writing and debugging code - **Critic**: Evaluates solutions and suggests improvements To run the multi-agent example: 1. Start the echo server: ```bash python examples/echo_server.py ``` 2. In a separate terminal, launch the multi-agent client: ```bash claude mcp-multi-agent examples/echo_server.py --config examples/agents_config.json ``` 3. Try these example interactions: - "I need to write a function that calculates the Fibonacci sequence" - "/talk Researcher What are the applications of Fibonacci sequences?" - "/talk Critic What are the efficiency concerns with recursive Fibonacci implementations?" - "/agents" (to see all available agents) - "/history" (to view the conversation history) ## Adding Your Own Examples Feel free to create your own MCP servers by following these steps: 1. Create a new Python file in this directory 2. Import FastMCP: `from fastmcp import FastMCP` 3. Create a server instance: `my_server = FastMCP("Server Name", description="...")` 4. Define tools using the `@my_server.tool` decorator 5. Define resources using the `@my_server.resource` decorator 6. Run your server with `my_server.run()` ### Creating Custom Agent Configurations To create your own agent configurations: 1. Create a JSON file with an array of agent definitions: ```json [ { "name": "AgentName", "role": "agent specialization", "model": "claude model to use", "system_prompt": "Detailed instructions for the agent's behavior and role" }, ... ] ``` 2. Launch the multi-agent client with your configuration: ```bash claude mcp-multi-agent path/to/server.py --config path/to/your_config.json ```