MCPs tagged with # language-models

Parallel Search MCP provides an interface to use the Parallel Search API seamlessly from any Model Context Protocol (MCP)-compatible language model client. It serves as a proxy server that connects requests to the search API, adding the necessary support for authentication and MCP compatibility. The tool is designed for everyday web search tasks and facilitates easy web integration for LLMs via standardized MCP infrastructure.

• ⭐ 3
• MCP
• parallel-web/search-mcp

Cross-LLM MCP Server is a Model Context Protocol (MCP) server enabling seamless access to a range of Large Language Model APIs including ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, and Mistral. It provides a unified interface for invoking different LLMs from any MCP-compatible client, allowing users to call and aggregate responses across providers. The server implements eight specialized tools for interacting with these LLMs, each offering configurable options like model selection, temperature, and token limits. Output includes model context details as well as token usage statistics for each response.

• ⭐ 9
• MCP
• JamesANZ/cross-llm-mcp

Unitree Go2 MCP Server is a server implementation based on the Model Context Protocol (MCP) that enables natural language command of the Unitree Go2 robot, interpreted by a large language model and translated into ROS2 instructions. This tool bridges AI-driven intent parsing with robot control through well-defined MCP functions. It includes configuration instructions for ROS2 environments, flexible integration with Claude Desktop and other AI systems, and direct interaction with the robot using contextual commands.

• ⭐ 55
• MCP
• lpigeon/unitree-go2-mcp-server

MCP Rubber Duck acts as an MCP (Model Context Protocol) server that enables users to query and manage multiple OpenAI-compatible large language models from a unified API. It supports parallel querying of various providers, context management across sessions, failover between providers, and response caching. This tool is designed for debugging and experimentation by allowing users to receive diverse AI-driven perspectives from different model endpoints.

• ⭐ 56
• MCP
• nesquikm/mcp-rubber-duck