# Model Interaction

The project aims to connect RAG applications to open-webui through the MCP protocol to achieve model context interaction, including basic PoC verification, knowledge base integration, and client docking.

This project is a command - line interface (CLI) tool that integrates Arcee AI, TESS, and MCP services. It adopts the Clean Architecture and DDD design principles to provide an abstract layer for unified access to multiple artificial intelligence services.

The Model Context Protocol (MCP) is a standardized protocol introduced by Anthropic for the interaction between large language models (LLMs) and external tools and functions, as well as for injecting context into LLMs. It enables models to request real-time information, perform operations in external systems, access professional knowledge bases, and interact with APIs and services. The MCP is similar to a USB hub, serving as a standard interface that reduces the risk of API changes because each MCP server is maintained by its own company, and users only need to integrate it. The MCP server provides three functions: tools, resources, and prompts.

xk6-mcp is a k6 extension for testing Model Context Protocol (MCP) servers, supporting interaction with MCP servers via stdio or SSE transmissions.

Ashra MCP is a model context protocol server designed for Ashra, supporting configuration and invocation through the Claude client.

MCP is a standardized protocol for interaction between AI models and applications, supporting tool invocation, resource management, and real-time data transfer.

An MCP server that provides model access to iTerm sessions, supporting efficient viewing of terminal output and full control.

mcp-kafka is a Kafka server implementation based on the Model Context Protocol (MCP), supporting interaction with Kafka ecosystem tools, including Kafka Connect, Burrow, and Cruise Control.

The MCP Python SDK is a Python development toolkit that implements the Model Context Protocol (MCP), allowing developers to build standardized MCP servers and clients to provide context data, tools, and interaction templates for LLM applications.

This project is an open-source project that builds an MCP (Model Context Protocol) server from scratch using Python. It supports custom packet handling, context management, and basic model integration, aiming to achieve efficient server interaction and communication.

An MCP server based on the Google Docs API that supports language models to create, search, append, and update Google documents.

A Model Context Protocol (MCP) implementation in Haskell, supporting interaction with clients such as Claude through StdIO and JSON-RPC, and providing resource, tool, and prompt management functions.

An MCP server that provides OpenAPI specification interaction services for large language models, supporting loading, exploring, and querying API structures

The MCP Server is an interaction system based on the Model Context Protocol standard, combining IPFS distributed storage and Claude AI processing capabilities to achieve efficient interaction between models, agents, and contextual data.

An MCP server designed for ChatGPT's memory function, supporting memory data sharing with other models. Requires environment configuration and application linking for use.

The AI MCP server is a bridge connecting AI models and computer systems, supporting system command execution, file operations, program control, and inter - model communication. It provides automated installation and the ability to integrate multiple AI models.

The MCP server project of VseGPT provides a standardized protocol for interaction between the language model and external services.

The IDA MCP Server is a model context protocol server for IDA interaction and automation, providing tools for reading the IDA database through large language models.

Laravel MCP is a Laravel package that implements the Model Context Protocol (MCP), providing a standardized communication interface between Laravel applications and AI assistants.

The Whoop MCP server is a Python service that provides access to the Whoop API, supporting queries for health data and interaction with language models.

The MCP Development Framework is a powerful toolset for interacting with large language models, providing functions such as file processing (PDF/Word/Excel) and web content retrieval. It supports Cursor IDE extension and has technical features such as intelligent file identification, efficient processing, and memory optimization.

MCP server development guide, introducing how to build a standardized communication protocol server for large language models (LLMs), including core architecture, function implementation, and example code.

An AI memory storage server based on knowledge graphs, providing persistent memory functions across interactions for AI models.

The MCP development framework is a powerful framework for creating custom tools to interact with large language models. It provides functions such as file processing and web content retrieval, supports multiple formats such as PDF, Word, and Excel, and has technical features such as intelligent recognition, efficient processing, and memory optimization.

The Hugging Face MCP Server is a model context protocol service that provides read-only access to the Hugging Face Hub API, enabling LLMs like Claude to interact with Hugging Face's models, datasets, spaces, papers, and collections.

iTerm-MCP is a server that provides model access for iTerm sessions, supporting efficient viewing of terminal output and full control.

This project provides MCP servers for integrating OpenAI's o1 model and Flux capabilities, supporting model interaction and image processing functions.