模型上下文协议服务器

C4Context
    title System Context Diagram for MCP Server

    Person(user, "User", "Developer or AI system user")
    
    System(mcpServer, "MCP Server", "AI access to secure internal systems - bridges AI models with external resources")
    
    System_Ext(ollama, "Ollama", "Local LLM service running Mistral model")
    System_Ext(jsonplaceholder, "JSONPlaceholder", "External REST API for testing and prototyping")
    
    Rel(user, mcpServer, "Sends natural language queries", "HTTP/REST")
    Rel(mcpServer, ollama, "Sends prompts and receives AI responses", "HTTP/REST")
    Rel(mcpServer, jsonplaceholder, "Fetches posts and comments", "HTTP/REST")
    
    UpdateRelStyle(user, mcpServer, $textColor="blue", $lineColor="blue")
    UpdateRelStyle(mcpServer, ollama, $textColor="green", $lineColor="green")
    UpdateRelStyle(mcpServer, jsonplaceholder, $textColor="orange", $lineColor="orange")

docker-compose.yml        # Docker Compose configuration with Ollama service
Dockerfile                # Dockerfile for building the app image
requirements.txt          # Python dependencies
.env.local               # Local development configuration
.env.docker              # Docker/production configuration
app/
    config.py             # Configuration management with environment support
    llm_agent.py          # LLM agent integration
    logger.py             # Logging setup
    main.py               # FastAPI application entry point
    router.py             # API routing with dependency injection
    adapters/             # Adapter plugins for external resources
        jsonplaceholder_comments.py
        jsonplaceholder_post.py
    prompts/              # System prompts for LLM agents
        system_prompt.txt
docker/
    ollama-entrypoint.sh  # Automated Ollama setup script
docs/
    c4-architecture.md    # Detailed C4 architecture diagrams

# Install dependencies
pip install -r requirements.txt

# Install Ollama (if not already installed)
# Download from: https://ollama.ai/download

# Setup Ollama with mistral model
ollama pull mistral
ollama run mistral

# Run the application
uvicorn app.main:app --host 0.0.0.0 --port 8080 --reload --env-file .env.local

# Start all services (includes Ollama with automatic mistral download)
docker-compose up --build

# This will:
    - Start Ollama service and automatically download mistral model
    - Build and start the MCP Server application
    - Set up internal Docker networking between services

# Get a post using natural language
curl -X POST http://localhost:8080/ask \
  -H "Content-Type: application/json" \
  -d '{"query":"Get me post number two"}'

# Get comments for that post
curl -X POST http://localhost:8080/ask \
  -H "Content-Type: application/json" \
  -d '{"query":"Now show me all comments for that post"}'

# Fetch post directly
curl -X POST http://localhost:8080/post-call \
  -H "Content-Type: application/json" \
  -d '{"post_id": 2}'

# Fetch comments directly
curl -X POST http://localhost:8080/comments-call \
  -H "Content-Type: application/json" \
  -d '{"post_id": 2}'