The Unity MCP Server is a C# - based Model Context Protocol (MCP) service used to connect the Unity editor with external large - language models (LLM) or cloud - based AI agents to achieve real - time automation and intelligent interaction.

Codebase MCP is a service that implements the Model Context Protocol (MCP), providing tools for retrieving and analyzing entire codebases through RepoMix, and supporting AI agents such as Cursor's Composer Agent to automatically read and understand large codebases.

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.

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.

The OpenFGA MCP Server is an experimental Model Context Protocol service that enables large language models to read from and write to the OpenFGA authorization store, providing fine-grained permission management capabilities for AI agents and developers.

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.

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.

This is a prototype of a code execution server based on the MCP protocol, which combines the code generation capabilities of large language models with MCP tool integration, enabling AI agents to run Python code in an isolated sandbox and invoke external tools.

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.

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 showcases multiple Model Context Protocol (MCP) servers integrated with Microsoft Azure, which enable large language models (LLMs) to securely access Azure tools and data sources, including AI agent services and various database services.

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.

An AI agent forwarding solution based on the MCP protocol that enables unified HTTP interface management of large model services, supporting multi-MCP Server integration and rapid deployment.

The Lightning Network MCP Server is a service that allows large language model agents to query Lightning Network node data through natural language. It supports gRPC and LNC connections and provides readable summaries and structured JSON output.

MCP is a tool that helps users build agents and complex workflows on the basis of large language models (LLMs).

An AI agent forwarding solution based on the MCP protocol, realizing unified HTTP interfaces and fast integration of large model services.

MCP Server and Tools is a project for building agents and complex workflows based on large language models (LLMs). It integrates with real - time data and tools through the Educhain library and supports the generation of educational content such as multiple - choice questions, lesson plans, and flashcards.

A web - based dialogue agent based on multiple large language models (such as Google Gemini, Anthropic Claude, etc.), which implements multi - step tool execution through the Vercel AI SDK and can interact with external services (such as WhatsApp, GitHub, etc.).