mcp-officer

mcp-officer

3.1

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The LSPD Interrogation MCP Server is a simulation server that uses Model Context Protocol and OpenAI's GPT-3.5-turbo model to create realistic police interrogation scenarios.

LSPD Interrogation MCP Server

A Model Context Protocol (MCP) based police interrogation simulation server powered by OpenAI.

📌 Key Features

  • MCP Integration:

    • Built using Model Context Protocol SDK
    • HTTP transport support
    • Dynamic resource management (officer-profile, conduct-interrogation)

  • OpenAI Integration:

    • Uses GPT-3.5-turbo model
    • Generates dynamic interrogation strategies
    • Simulates suspect responses
    • Creates realistic dialogue flows

  • Core Components:

    • Police officer profile management
    • Smart interrogation mechanics
    • Suspect behavior simulation
    • Crime type and evidence integration

🚀 Installation

pnpm install
# Required environment variables
cp .env.example .env
# Start server
pnpm start

⚙️ Configuration

.env file:

OPENAI_API_KEY=your_api_key_here

Configurable parameters in config.ts:

  • AI model selection
  • Maximum token count
  • Temperature parameter (creativity level)

🌐 API Endpoints

Officer Profile

GET /profile/:badgeNumber

curl http://localhost:3000/profile/1234

Start Interrogation

POST /interrogations/{suspectId}

{
  "suspectName": "John Doe",
  "pressureLevel": 75,
  "crime": "Armed robbery",
  "evidence": ["Fingerprint", "Security camera footage"]
}

Suspect Response

POST /interrogations/{suspectId}/respond

{
  "suspectName": "John Doe",
  "officerStatement": "Your fingerprints were found at the crime scene!",
  "guilt": 85,
  "personality": "cowardly",
  "previousResponses": ["I'm innocent!"]
}

🔍 Example Usage

# Get officer profile
curl http://localhost:3000/profile/1234

# Start interrogation
curl -X POST http://localhost:3000/interrogations/suspect_01 \
  -H "Content-Type: application/json" \
  -d '{
    "suspectName": "John Doe",
    "pressureLevel": 80,
    "crime": "Drug trafficking",
    "evidence": ["Search records", "Confidential witness statement"]
  }'

✅ Data Validation

All endpoints include strong type checking and validation using Zod library:

  • Pressure Level: 0-100 (required)
  • Suspect Name: string format
  • Evidence: string array (optional)

🔒 Security

  • Sensitive data (OpenAI API key) managed through environment variables
  • HTTPS enforcement in production
  • Secure input handling with request validation

🤝 Contribution

  1. Fork the repository
  2. Create new branch (feat/my-feature or fix/issue-number)
  3. Commit your changes
  4. Push to the branch
  5. Open a Pull Request

📜 License

Distributed under the MIT License.