MCP-LLM Bridge

what is MCP-LLM Bridge? MCP-LLM Bridge is a TypeScript implementation that connects local Large Language Models (LLMs) via Ollama to Model Context Protocol (MCP) servers, enabling the use of advanced tools similar to those used by Claude. how to use MCP-LLM Bridge? To use the MCP-LLM Bridge, install the Ollama and MCP servers, configure the necessary credentials, and start the bridge. You can then send prompts or commands to interact with your local LLM and leverage MCP capabilities. key features of MCP-LLM Bridge? Multi-MCP support with dynamic tool routing Structured output validation for tool calls Automatic tool detection based on user input Comprehensive logging and error handling Full integration with local models for various tasks including web search and email management use cases of MCP-LLM Bridge? Managing files and directories through local commands Conducting web searches with Brave Search Sending and managing emails via Gmail integration Image generation through Flux Interacting with GitHub repositories FAQ from MCP-LLM Bridge? How do I set up the MCP-LLM Bridge? Install Ollama, required MCP servers, set the appropriate credentials, and configure the bridge using bridge_config.json. Can this bridge work with any local LLM? Yes, as long as the LLM is compatible with the Ollama framework. Is it necessary to have an internet connection? No, once set up, the bridge operates entirely locally, utilizing open-source models.

As an MCP (Model Context Protocol) server, MCP-LLM Bridge enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use the MCP-LLM Bridge, install the Ollama and MCP servers, configure the necessary credentials, and start the bridge. You can then send prompts or commands to interact with your local LLM and leverage MCP capabilities. key features of MCP-LLM Bridge? Multi-MCP support with dynamic tool routing Structured output validation for tool calls Automatic tool detection based on user input Comprehensive logging and error handling Full integration with local models for various tasks including web search and email management use cases of MCP-LLM Bridge? Managing files and directories through local commands Conducting web searches with Brave Search Sending and managing emails via Gmail integration Image generation through Flux Interacting with GitHub repositories FAQ from MCP-LLM Bridge? How do I set up the MCP-LLM Bridge? Install Ollama, required MCP servers, set the appropriate credentials, and configure the bridge using bridge_config.json. Can this bridge work with any local LLM? Yes, as long as the LLM is compatible with the Ollama framework. Is it necessary to have an internet connection? No, once set up, the bridge operates entirely locally, utilizing open-source models.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.