Allows using OpenAI's models for text generation via the Model Context Protocol, requiring an API key for authentication.
Provides type safety throughout the application with Pydantic validation for request and response data.
Stores conversation history in a SQLite database with WAL mode and optimized indexes for high performance.
Uses YAML for configuration of LLM providers and settings in the src/config.yaml file.
MCP Platform
High-performance Model Context Protocol (MCP) client with WebSocket API, SQLite storage, and support for OpenRouter, OpenAI, and Groq.
🚀 Quick Start
Connect: ws://localhost:8000/ws/chat
📡 WebSocket API
Send:
Receive:
⚙️ Configuration
LLM Provider (src/config.yaml
)
MCP Servers (src/servers_config.json
)
📁 Key Files
src/config.yaml
- LLM providers and settingssrc/servers_config.json
- MCP server configurationschat_history.db
- SQLite database for conversation history
✅ Features
- Full MCP Protocol - Tools, prompts, resources
- High Performance - SQLite with WAL mode, optimized indexes
- Real-time Streaming - WebSocket with delta persistence
- Multi-Provider - OpenRouter (100+ models), OpenAI, Groq
- Type Safe - Pydantic validation throughout
Requirements: Python 3.13+, request_id
required in WebSocket messages
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
High-performance Model Context Protocol server supporting multiple LLM providers (OpenRouter, OpenAI, Groq) with WebSocket API and conversation history persistence.
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