HiveChat is an AI chat application designed for small and medium - sized teams. It supports multiple large - model service providers and provides functions such as group management, Token limits, and third - party login.

Model Context Protocol (MCP) .NET sample library, demonstrating how to use the MCP protocol to standardize the context interaction of large language models (LLMs) in .NET applications. It includes examples such as a YouTube subtitle extractor, supports flexible switching of LLM providers, and enables the construction of AI workflows.

An MCP server application built on the Apache Superset REST API, enabling database query operations through large models

Okta MCP Server is a server based on the Model Context Protocol that allows large - language models and AI agents to manage Okta organizations through natural language instructions, supporting management operations such as users, groups, applications, policies, and logs.

An MCP server application built on the Apache Superset REST API, implementing database query functions through large models

MCP-Memos is a memo tool based on the MCP protocol, designed specifically for developers. It supports quick recording and retrieval of text information without switching applications. It uses large language models to provide powerful fuzzy search capabilities, including semantic understanding, context awareness, and natural language query functions.

OtterBridge is a lightweight MCP server used to connect applications with multiple large language model providers, supporting models such as Ollama, with a simple and flexible design.

MCP Palette is a desktop application for managing Model Context Protocol server configurations, providing a centralized interface to configure, manage, and deploy MCP servers for large language models.

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions for large language models, including a tiered memory architecture, multiple memory types, and semantic search features.

File Context MCP is a TypeScript-based application that provides an API to query large language models (LLMs) through local file content. It supports multiple LLM providers (Ollama and Together.ai) and can process multiple file types to generate context-aware responses.

This project implements an MCP server for interacting with the Wolfram Alpha API, enabling chat applications to perform calculation queries and obtain structured knowledge. It includes an MCP client example based on Gemini, demonstrating how to connect a large - language model to the MCP server for real - time interaction with the Wolfram Alpha knowledge engine.

The Baidu Cloud Vector Database MCP Server is a server that provides access to the functionality of Baidu Cloud Vector Database, supporting cooperation with multiple large language model applications.

GUARDRAIL is a security framework specifically designed for the large language model (LLM) application ecosystem, providing comprehensive protection especially for the Model Context Protocol (MCP). It uses a multi - layer architecture, including an information gateway layer, a context verification layer, a request control layer, an execution isolation layer, and an audit monitoring layer, aiming to prevent data leakage, unauthorized access, and resource abuse. This framework emphasizes progressive adoption, allowing developers to gradually enhance security while maintaining high performance and ease of use.

This project implements a ClickHouse MCP server for seamless integration of the ClickHouse database with AI applications such as large language models (LLMs), supporting functions such as querying databases and obtaining table structures.

Tome is a MacOS application (support for Windows and Linux is coming soon) developed by the Runebook team. It aims to simplify the use of local large language models (LLMs) with MCP servers. By integrating Ollama and managing MCP servers, users can quickly start chatting with MCP-powered models without dealing with complex configurations.

The Wanaku MCP router is an AI application router based on the Model Context Protocol (MCP), aiming to standardize the way applications provide context to large language models (LLMs).

The openEuler MCP Servers repository is a repository for storing various MCP Servers, aiming to call various applications through the general large model context protocol (MCP) to expand the capabilities of large models, especially in the operating system field.

A Model Context Protocol (MCP) tool implemented in Python, used to handle communication between applications and large language models (LLMs), and obtain the exchange rates of specified currencies against the Swedish Krona through the Riksbanken API.

A minimalist implementation of the Model-Context-Protocol (MCP) pattern for building scalable applications absorbable by Large Language Models (LLMs).

This project provides a series of Model Context Protocol (MCP) server implementations based on the Quarkus framework, used to extend the capabilities of large language model (LLM) applications that support MCP. It includes various services such as JDBC databases, file systems, JavaFX drawing, Kubernetes, and containers.

An intelligent conversational robot project based on large models, supporting multi - platform access and multiple AI models, with text, voice, image processing, and plugin expansion capabilities, and can customize enterprise AI applications.

AytchMCP is a model context protocol server for Aytch4K applications, supporting interactions with multiple large language models and including functions such as resource management, tool components, and protocol processing.

This is a list of multiple open - source AI projects, covering multiple fields such as automated agents, large - language models, image generation, and AI development frameworks. These projects aim to help developers make money using AI technology, including building intelligent assistants, automating workflows, and content generation applications.

The Squad MCP server is a protocol service that connects the Squad product discovery platform with large language model applications, providing a rich toolset for creating, querying, and updating product strategy artifacts directly from an AI assistant.

This project is an MCP server designed to help large language models (LLMs) accurately obtain Quranic text through the Quran API and avoid generating incorrect content. It provides an integration solution with the Claude desktop application and enables accurate Quranic verse queries through a local server.

This project is a server - side based on the Model Context Protocol (MCP), providing a bridge for the Brandfetch API, enabling large language model (LLM) applications to search for brands and obtain detailed information.

A cross - platform desktop application based on Electron that connects to multiple large language models via the MCP protocol, providing a simple and efficient interaction interface.