# AI integration

The PJE MCP Server is a service for integrating with the Brazilian Electronic Justice System (PJE), supporting A1 and A3 digital certificates, providing functions such as case management, judicial data query, and multi-court support, and achieving native AI integration with Claude Desktop.

An MCP server that connects AI assistants with the Metabase analytics platform, providing functions such as data query and dashboard access, and supporting two authentication methods.

The Oxylabs MCP Server provides web data crawling services for AI assistants, supporting dynamic rendering, structured extraction, and anti - blocking functions.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers and implement OAuth login functionality, supporting connection and tool invocation through the MCP inspector and the Claude desktop application.

MCP Linear is a Model Context Protocol server that implements the Linear GraphQL API, enabling AI assistants to interact with the Linear project management tool.

A profile analysis tool based on the LinkedIn API that interacts with Claude AI through the MCP protocol to achieve the functions of obtaining, analyzing, and searching LinkedIn post data.

The Uptime Agent MCP Server is a service that connects the Uptime Agent monitoring system to an AI assistant (such as Claude) via the Model Context Protocol (MCP), supporting functions such as real - time monitoring access, incident management, and monitoring creation.

The Amplitude MCP Server is a Model Context Protocol (MCP) server for integrating Amplitude analytics into AI workflows, supporting functions such as event tracking, page views, user registration, setting user properties, and revenue tracking.

The Kubernetes MCP Server is a server based on the Model Context Protocol. It provides seamless integration with the Kubernetes API, supports interacting with Kubernetes clusters through natural language, and realizes functions such as resource query, monitoring, and operation.

A professional server that combines 3D cartoon image generation and file system management, providing high-quality 3D cartoon generation based on Gemini AI and secure file operation functions.

An MCP server implementation based on Spring Boot and Spring AI, enabling AI agents to search and navigate files and folders in Microsoft OneDrive.

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.

The Razorpay MCP Server is a middleware connecting the Razorpay payment gateway and AI assistants. Through the standardized Model Context Protocol, AI assistants can directly access Razorpay account data.

This project is a Python tutorial practice on how to create an MCP server. You can add and manage the MCP server through the Claude command-line tool, and it supports testing and debugging of AI functions such as the ChromaDB vector database.

The Strapi MCP Server is a Model Context Protocol server designed for Strapi CMS, providing a standardized AI assistant interaction interface and supporting content type management and REST API operations.

UML-MCP is a server that supports multiple diagram generations. It enables seamless integration with AI assistants through the MCP protocol and provides the function of generating multiple diagram types such as UML and Mermaid.

The Explorium MCP Server is a service based on the Model Context Protocol that connects AI assistants to the Explorium business database and provides enterprise data query functionality.

An MCP server that connects AI assistants to the Solana blockchain, providing blockchain interaction functions such as smart contract development, account management, and transaction processing

An MCP server that provides real-time Cointelegraph news, supporting multi-category RSS subscriptions, article summary conversion, and caching functions, and can be integrated with Claude Desktop.

AI and MongoDB integrated MCP server project based on Spring Boot

Shell MCP Server is a tool that provides secure Shell command execution capabilities for AI applications, supports multiple Shell environments, and has security features such as directory isolation and timeout control.

Supabase MCP Server is a tool that connects Supabase projects with AI assistants (such as Cursor, Claude, etc.), enabling AI assistants to directly manage database tables, query data, and perform other functions through the Model Context Protocol standard.

Home Assistant MCP is a standardized protocol server that provides a secure and typed interface for AI assistants to interact with the smart home system, supporting device control, status query, and automated management.

This project enhances Claude's ability to handle complex tasks by integrating the reasoning engine of DeepSeek R1, providing support for multi-step precise reasoning.

HWP-MCP is a protocol service that enables AI models to control HWP documents, supporting document creation, editing, and automation processing.

A server implementation for managing UniFi network devices through the MCP protocol, supporting natural language interaction and AI proxy control.

This project provides a Python - based MCP server for integrating OSV (open - source vulnerability) data with AI assistants or large - language models, and exposes tools and resources through the MCP protocol to enhance the workflows and capabilities of LLMs.

The Windows Command Line MCP Server is a secure intermediary service that allows AI models to interact with the Windows system under strict security control, including functions such as executing commands, creating projects, and obtaining system information.

XTQuantAI is a server based on the MCP protocol that integrates the Xuntou Quantitative Platform with an AI assistant, enabling the AI to directly access and operate quantitative trading data.

This project demonstrates how to integrate Model Context Protocol (MCP) tools with Microsoft Semantic Kernel to achieve seamless interaction between AI models and external data sources or tools. By standardizing the interaction between applications and AI models through the MCP protocol and combining the powerful functions of Semantic Kernel, developers can expand AI capabilities, dynamically call external functions, and simplify the orchestration of complex workflows.