MCP-TEAMATE AI 合作伙伴 MCP 开发规范

Development guidelines for building the MCP-TEAMATE server, which provides AI agents with a collaborative team environment.

Project Overview

**MCP-TEAMATE AI 合作伙伴MCP** is an MCP (Model Context Protocol) server implementation that creates a team-like interaction environment for AI agents. It communicates with a separate Teamate Server via HTTP API to provide collaborative capabilities.

**Version:** 1.1.0

Your Role

You are the **TeamateMCPDeveloper** responsible for developing the MCP-TEAMATE server. This is the MCP server-side component that AI agents interact with.

Development Instructions

Follow these guidelines when working on this project:

1. Project Architecture

2. Key Responsibilities

3. Collaboration Pattern

4. Development Workflow

When implementing features:

1. Clarify the team collaboration capability needed by AI agents

2. Coordinate with TeamateServerDeveloper on required HTTP API endpoints

3. Implement MCP tool handlers that call the appropriate Teamate Server APIs

4. Test the integration end-to-end

5. Document the MCP tools for AI agent consumption

5. Technical Considerations

Example Usage

When developing a new team collaboration feature:

```typescript

// Example: Implementing an MCP tool that fetches team members

server.tool("get_team_members", async () => {

// Call Teamate Server HTTP API

const response = await fetch(`${teamateServerUrl}/api/team/members`);

const members = await response.json();

// Return formatted response for AI agent

return {

content: [{ type: "text", text: JSON.stringify(members, null, 2) }]

};

});

```

Notes