# Data integration

The Xero MCP Server is a middleware service that connects to Xero accounting software, allowing clients to interact with Xero through a toolset.

This project demonstrates the implementation of the Model Context Protocol (MCP) in a blog application system, including a TypeScript MCP server, a simulated book service, and a Python client, enabling seamless integration of language models and structured data operations.

Whole-network hot trend aggregation service based on the MCP protocol

Supermemory is an AI-driven memory engine designed to provide contextual knowledge for LLMs by integrating personal data, enabling intelligent management and retrieval of information.

The LeanIX MCP integration project provides an MCP server that connects LeanIX with AI assistants. It exposes the functions of LeanIX's GraphQL API through 5 MCP tools, including viewing statistics, searching, subscription management, creating, and updating data sheets.

An MCP server designed for the Indian stock market (NSE/BSE), integrating MongoDB and the Alpha Vantage API, providing portfolio analysis, stock recommendations, and market trend insights services.

This project implements a Model Context Protocol (MCP) server, exposing the Databricks Genie API functionality as a tool. It supports querying Databricks data in natural language and can be integrated with MCP clients such as Claude Desktop.

The RISKEN MCP server is a protocol server that provides RISKEN API integration, supporting automated data acquisition, scanning, and analysis, as well as building AI tool applications.

The MCP Partner Hub is a resource library that centrally displays and compares MCP (Model Context Protocol) servers provided by different ISV partners, aiming to help users discover, evaluate, and select MCP servers that meet their needs.

MCP (Model Context Protocol) is a standardized protocol for providing context connection between AI applications and LLMs, similar to the USB - C interface for AI applications. This project provides a guide for building a custom MCP server, supports integration with tools such as Claude Desktop, and enables access to local data sources and remote services.

A Pokémon Q&A assistant based on RAG technology, integrating the PokeAPI database and AI capabilities to provide accurate information interaction

MCP Server Go is a Model Context Protocol (MCP) server implemented in Go, used to connect LLM applications with external data sources and tools, providing a simple and efficient development experience.

This project is a tool that allows LLMs to directly access Google Spreadsheet data through a Model Context Protocol (MCP) server, providing functions such as spreadsheet information retrieval, data format conversion, and integration with MCP clients.

Claude MCP installation tool for marketing professionals, including 8 core services to expand AI capabilities

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.

Flex MCP Agent is a multi - functional agent project that integrates weather data acquisition, Confluence interaction, and email sending functions, standardizing the interaction between AI models and data sources using the Model Context Protocol (MCP).

Snowflake MCP Service is a server that implements the Model Context Protocol (MCP), providing the ability for MCP-compatible clients to access Snowflake databases. It supports two authentication methods: password and key pair, and includes core functions such as connection management and query processing.

iMCP is a macOS application that connects users' digital lives through AI. It supports interaction with clients such as Claude Desktop via the Model Context Protocol (MCP), providing multiple functions such as calendar, contacts, location, maps, messages, reminders, and weather.

This project demonstrates how to integrate an AI agent powered by Azure OpenAI with the Microsoft Fabric data warehouse through the Model Context Protocol (MCP), using GraphQL as a common data connection layer to achieve bidirectional access to enterprise data.

A basic project for developing custom MCP servers, providing a complete architectural pattern, example tools, and development infrastructure to support AI assistants in connecting to external data sources or APIs.