The Alpaca MCP server is a model context protocol (MCP) service that implements the Alpaca trading API, allowing large language models to interact with the Alpaca trading system through natural language, supporting stock/options trading, portfolio management, and real-time market data acquisition.

awesome - mcp is a project that collects Model Context Protocol (MCP) servers/clients, aiming to simplify the integration of large language models with external systems through a standardized protocol.

MacPilot CLI is an open-source tool that enables large language models to interact with the macOS system through the MCP protocol, providing system operation functions.

GraphRAG MCP is a hybrid retrieval system that combines the Neo4j graph database and the Qdrant vector database, providing document retrieval services that combine semantics and graph relationships for large language models.

The ChatData MCP Server is a framework based on the Model Control Protocol, providing a toolset, prompt system, and resource management to enhance the capabilities of large language models.

The Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers. It aims to provide large language models (LLMs) with secure and controllable access to tools and data sources. These servers demonstrate the diversity and scalability of MCP, covering various functions from file system operations to database integration, from web search to AI image generation.

The MCP Logical Solver is a powerful reasoning system that combines large language models and formal theorem - proving capabilities. It supports natural language and first - order logic input, performs automatic verification through Prover9/Mace4, and provides structured reasoning and explanations.

The MoviePilot MCP server is a protocol implementation that connects large language models with the MoviePilot media library management system, supporting media search, subscription management, download control and other functions through natural language interaction.

An MCP server that provides file system context for large language models, supporting file operations, code analysis, and intelligent search.

The Astra DB MCP server is a service that provides large language models (LLMs) with the ability to interact with the Astra database, extending the functions of LLMs as agents to interact with external systems.

This project is a collection of Model Context Protocol (MCP) servers specifically designed for DevOps tools and platforms. It enables large language models (LLMs) to directly interact with mainstream DevOps systems in a standardized way, achieving automated control of operations such as infrastructure, deployment pipelines, and monitoring.

This project builds a Retrieval Augmented Generation (RAG) server based on IBM Watsonx.ai, uses ChromaDB for vector indexing, and exposes interfaces through the Model Context Protocol (MCP). The system can process PDF documents and answer questions based on the document content, realizing an intelligent question answering function that combines large language models with specific domain knowledge.

A server that converts traditional Web APIs into MCP tools, supporting batch API registration and request header management, simplifying the docking between business systems and large models.

The SingleStore MCP Server is a service based on the Model Context Protocol (MCP) for managing context between large language models (LLMs) and external systems. It supports interacting with SingleStore through natural language and simplifies complex operations.

The Cloudflare MCP service is a standardized protocol based on the Model Context Protocol (MCP) for managing context interactions between large language models (LLMs) and external systems. This project provides an installer and an MCP server, supporting the management of various resources in a Cloudflare account, such as Workers, KV storage, R2 storage, and D1 databases, through natural language instructions. Users can perform various operations in a Cloudflare account using natural language via MCP clients such as Claude Desktop, VSCode (Cline), and Windsurf.

MCP Tools is a server project that implements the Model Context Protocol (MCP), providing file system and command execution tools for LLM clients such as Claude Desktop, and extending the local system interaction capabilities of large language models.

The Model Context Protocol (MCP) is an open - source protocol released by Anthropic, aiming to solve the standardization problem of connecting large language models (LLMs) with external data sources and systems. It provides a structured framework that enables models to integrate and utilize external context, thereby expanding their capabilities and improving response accuracy. MCP supports functions such as knowledge expansion, external tool calls, and pre - written prompts.

An MCP server that combines Claude Code and Google Gemini AI to achieve in - depth code analysis through multi - model collaboration. Claude is good at local context operations and CLI workflows, while Gemini uses its ultra - large context window for distributed system debugging and long - trace analysis.

Agent Farm v3.4 is a system based on AI agent evolution and parallel task execution, which realizes task processing through tool - enhanced agents. The new version introduces the chunked write mode, supports the parallel generation of large documents and code files, improves performance by 8.6 times, and uses local models for result synthesis without relying on cloud tokens.

A natural language MySQL database query system based on MCP and the QWEN large model, providing GUI interface support

A multi-agent deep research system based on MCP, integrating LinkUp search, CrewAI coordination, and the Gemini large model, providing an interactive interface through Streamlit.

Auto Causal Inference is a project that uses large language models (LLMs) to automatically perform causal inference. Users only need to specify the treatment variable and the outcome variable, and the system can automatically complete the full - process analysis, including variable role identification, causal graph construction, effect estimation, and model validation. The project provides two agent architectures (LangGraph and MCP) to achieve this function, which is particularly suitable for causal problem analysis in the banking scenario.

MacPilot CLI is an open-source tool that allows large language models to interact with the macOS system through the MCP protocol, providing system operation functions.

The Unified MCP Tool Graph is a research - driven project that provides an intelligent infrastructure layer for large language models (LLMs) and agent AI systems to dynamically retrieve the most relevant tools by aggregating and structuring tool APIs from different MCP servers into a centralized Neo4j graph database.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. The project includes implementations of various functional servers, covering areas such as file systems, databases, search, and API integration, and supports development with TypeScript and Python SDKs.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. This project includes various types of server implementations, covering multiple domains such as file systems, databases, Git, and Slack, and supports TypeScript and Python SDKs.

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.

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.

BRAINS OS is an AI operating system based on modern cloud-native technologies, designed specifically for managing large language models and dedicated AI agents, providing visual workflow editing, a unified command system, and a secure deployment framework.

This project is an implementation of an MCP server based on ODBC, providing large language models with the ability to transparently access ODBC data sources through TypeScript and node - odbc. It supports multiple database management systems, including Virtuoso, and provides a rich set of tools for data query and management.

Clo MCP is an integrated system that connects Clo3D with large language models, enabling AI-assisted fashion design and scene manipulation through the model context protocol.

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.

A server that provides file system context for large language models, supporting file operations, code analysis, and intelligent caching.

The Baichuan website security monitoring system is a site monitoring tool based on large models, providing website availability detection, SSL certificate management, path scanning, and group management functions.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes server implementations with various functions, such as file system operations, database access, Git management, Slack integration, etc., and supports TypeScript and Python SDKs.

The HUDU MCP Server is a model context protocol server integrated with the HUDU technical documentation and customer information management system, allowing large language models to obtain customer account information, knowledge base articles, asset data, etc. through API interaction.

MCP Tools is a collection of Model Context Protocol servers that provide interfaces to various SaaS tools and services, enabling large language models to interact with external systems and APIs.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers for providing large language models (LLMs) with secure and controlled access to tools and data sources. The project includes various functional servers, such as file system operations, Git integration, database access, etc., and supports rapid development of new services through TypeScript and Python SDKs.

A RAG system built with open-source embedding models, vector databases, and the Gemini large language model, supporting local document processing and dynamic index update.

Provide structured argumentation tools to support systematic dialectical reasoning and argument analysis, and help large language models conduct complex problem assessment and multi - perspective argumentation.