A simple MCP server that provides a unified interface to various LLM providers using Pydantic AI
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# LLM Bridge MCP [](https://smithery.ai/server/@sjquant/llm-bridge-mcp) LLM Bridge MCP allows AI agents to interact with multiple large language models through a standardized interface. It leverages the Message Control Protocol (MCP) to provide seamless access to different LLM providers, making it easy to switch between models or use multiple models in the same application. <a href="https://glama.ai/mcp/servers/@sjquant/llm-bridge-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@sjquant/llm-bridge-mcp/badge" alt="LLM Bridge MCP server" /> </a> ## Features - Unified interface to multiple LLM providers: - OpenAI (GPT models) - Anthropic (Claude models) - Google (Gemini models) - DeepSeek - ... - Built with Pydantic AI for type safety and validation - Supports customizable parameters like temperature and max tokens - Provides usage tracking and metrics ## Tools The server implements the following tool: ``` run_llm( prompt: str, model_name: KnownModelName = "openai:gpt-4o-mini", temperature: float = 0.7, max_tokens: int = 8192, system_prompt: str = "", ) -> LLMResponse ``` - `prompt`: The text prompt to send to the LLM - `model_name`: Specific model to use (default: "openai:gpt-4o-mini") - `temperature`: Controls randomness (0.0 to 1.0) - `max_tokens`: Maximum number of tokens to generate - `system_prompt`: Optional system prompt to guide the model's behavior ## Installation ### Installing via Smithery To install llm-bridge-mcp for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@sjquant/llm-bridge-mcp): ```bash npx -y @smithery/cli install @sjquant/llm-bridge-mcp --client claude ``` ### Manual Installation 1. Clone the repository: ```bash git clone https://github.com/yourusername/llm-bridge-mcp.git cd llm-bridge-mcp ``` 2. Install [uv](https://github.com/astral-sh/uv) (if not already installed): ```bash # On …
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