Wren Engine is a semantic engine designed for MCP clients and AI agents, providing semantic layer support to enable AI to accurately understand enterprise data models and business logic. It supports multiple data sources and is embedded in MCP clients to ensure the accuracy and governance of data interaction.

Proxy Feishu robots through the MCP server to achieve the integration of business logic between LLM models such as Claude/Cursor and Feishu robots

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.

MCP-ANY-REST is a REST API connector based on the Model Context Protocol standard. It enables secure and efficient connection between AI models and business systems through the ZML configuration language, supporting service orchestration and token authentication.

This project is a developer documentation about the Model Context Protocol (MCP) Server, which details how to build, run, and integrate the MCP Server to achieve a secure connection between AI models and real-time data, tools, and business logic.

The Triplewhale MCP Server is a server based on the Model Context Protocol (MCP) standard, used to connect large language models (such as Claude) with the Triplewhale platform to achieve business data query and analysis functions through natural language.

The Triplewhale MCP Server is a server based on the Model Context Protocol (MCP) standard, used to connect large language models (such as Claude) to the Triplewhale platform, enabling business data query and analysis through natural language.

An open - source project researching the integration of Retrieval Augmented Generation (RAG) with Multi - Cloud Processing (MCP) servers, focusing on the application of free models in business software and providing a modular learning path and practical cases.