# MCP Quick Start Guide ## Prerequisites - .NET 8 SDK - Node.js 18+ - At least one LLM API key (Gemini, OpenAI, or Claude) ## Setup Steps ### 1. Configure LLM API Keys Add your API key to `appsettings.Development.json` or user secrets: ```json { "Llm": { "Claude": { "ApiKey": "YOUR_CLAUDE_API_KEY_HERE" } } } ``` Or use .NET user secrets (recommended): ```bash cd src/Managing.Api dotnet user-secrets set "Llm:Claude:ApiKey" "YOUR_API_KEY" ``` Or use environment variables: ```bash export Llm__Claude__ApiKey="YOUR_API_KEY" dotnet run --project src/Managing.Api ``` ### 2. Build the Backend ```bash cd src dotnet build Managing.sln ``` ### 3. Run the Backend ```bash cd src/Managing.Api dotnet run ``` The API will be available at `https://localhost:7001` (or configured port). ### 4. Generate API Client (if needed) If the LLM endpoints aren't in the generated client yet: ```bash # Make sure the API is running cd src/Managing.Nswag dotnet build ``` This will regenerate `ManagingApi.ts` with the new LLM endpoints. ### 5. Run the Frontend ```bash cd src/Managing.WebApp npm install # if first time npm run dev ``` The app will be available at `http://localhost:5173` (or configured port). ### 6. Test the AI Chat 1. Login to the application 2. Look for the floating chat button in the bottom-right corner 3. Click it to open the AI chat 4. Try these example queries: - "Show me my backtests" - "Find my best performing strategies" - "What are my BTC backtests?" - "Show backtests with a score above 80" ## Getting LLM API Keys ### Anthropic Claude (Recommended - Best for MCP) 1. Go to [Anthropic Console](https://console.anthropic.com/) 2. Sign in or create an account 3. Navigate to API Keys and create a new key 4. Copy and add to configuration 5. Note: Requires payment setup ### Google Gemini (Free Tier Available) 1. Go to [Google AI Studio](https://makersuite.google.com/app/apikey) 2. Click "Get API Key" 3. Create a new API key 4. Copy and add to configuration ### OpenAI 1. Go to [OpenAI Platform](https://platform.openai.com/api-keys) 2. Create a new API key 3. Copy and add to configuration 4. Note: Requires payment setup ### Anthropic Claude 1. Go to [Anthropic Console](https://console.anthropic.com/) 2. Create an account and API key 3. Copy and add to configuration 4. Note: Requires payment setup ## Architecture Overview ``` User Browser ↓ AI Chat Component (React) ↓ LlmController (/api/Llm/Chat) ↓ LlmService (Auto-selects provider) ↓ Gemini/OpenAI/Claude Provider ↓ MCP Service (executes tools) ↓ BacktestTools (queries data) ``` ## Troubleshooting ### No providers available - Check that at least one API key is configured - Verify the API key is valid - Check application logs for provider initialization ### Tool calls not working - Verify `IBacktester` service is registered - Check user has backtests in the database - Review logs for tool execution errors ### Frontend errors - Ensure API is running - Check browser console for errors - Verify `ManagingApi.ts` includes LLM endpoints ### Build errors - Run `dotnet restore` in src/ - Ensure all NuGet packages are restored - Check for version conflicts in project files ## Example Queries ### Simple Queries ``` "Show me my backtests" "What's my best strategy?" "List all my BTC backtests" ``` ### Filtered Queries ``` "Find backtests with a score above 85" "Show me backtests from the last 30 days" "List backtests with low drawdown (under 10%)" ``` ### Complex Queries ``` "What are my best performing ETH strategies with a winrate above 70%?" "Find backtests using RSI indicator sorted by Sharpe ratio" "Show me my top 5 backtests by growth percentage" ``` ## Next Steps - Add more MCP tools for additional functionality - Customize the chat UI to match your brand - Implement chat history persistence - Add streaming support for better UX - Create custom tools for your specific use cases ## Support For issues or questions: 1. Check the logs in `Managing.Api` console 2. Review browser console for frontend errors 3. Verify API keys are correctly configured 4. Ensure all services are running ## Additional Resources - [MCP Architecture Documentation](./MCP-Architecture.md) - [Implementation Summary](./MCP-Implementation-Summary.md) - [Model Context Protocol Spec](https://modelcontextprotocol.io)