Go-based MCP chat bot with Gin, designed for flexible routing of conversations across multiple AI models via the Model Context Protocol. It provides a responsive web UI, MCP integration, and in-process history, ideal for rapid experiments and demonstrations with different models in a local or small-team environment.

A Model Context Protocol(MCP) server for echo message

Python-based demonstration of the Model Context Protocol, showcasing tools, data, and prompts through a weather-focused example.

TypeScript bridge enabling automated GitHub repository management via protocol-style tools, including creation, commits, and sync operations.

Open, extensible protocol for standardizing how apps provide context to large language models, enabling plug-and-play data sources and tools.

Native integration enabling natural language database queries and subscribed data shares with local setup.

GitHub Projects API integration enabling views, priorities, dependencies, and metrics management with Docker, NPX, and library usage.

Doc retrieval platform enabling AI tools to access up-to-date docs across libraries like LangChain, LlamaIndex, and OpenAI, through dynamic web search, targeted URL discovery, and HTML content extraction. The configuration-driven design makes it easy to extend to additional libraries and documentation sources.

Model Context Protocol Servers with SSE

TypeScript-based integration tool for PocketBase that lists collections, with easy config, admin authentication, and debugging support.

Connects LLMs to Azure AI Foundry resources via a secure MCP server with search and grounding tools.

Lightweight Go MCP server that exposes Meilisearch search, index management, and documents to LLMs.

Go-based tool enabling dynamic GraphQL queries, mutations, and schema introspection with header customization for secure API access.

O Model Context Protocol (MCP) é um protocolo aberto desenvolvido pela Anthropic para padronizar a integração entre modelos de inteligência artificial (IA) e fontes de dados ou ferramentas externas.

MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.

Unified Flow blockchain access with balance checks, domain resolution, script execution, and transaction handling via a standardized interface and configurable networks.

Weather-focused MCP delivering forecasts, flood warnings, water levels, and earthquake news via Malaysia open data for LLMs.

Exposes Cloudinary Upload and Admin API actions as AI-accessible tools for seamless asset management and automated media workflows.

An integrated Aptos development toolkit with doc browsing, project generation, component scaffolding, contract testing, and ABI generation to streamline end-to-end app creation.

Unifies Linear issue tracking with a flexible protocol to empower LLMs to manage issues, projects, teams, and milestones with rich interactions.

Serverless MCP server enabling tool registration, in-memory client-server, and context-aware credential handling for secure, rapid tool execution.

MailPace MCP Server enables sending emails via MailPace's fast transactional API with a streamlined send-email tool and Smithery deployment.

Connects Tibber energy data to AI agents for price queries, consumption insights, and intelligent analytics via an accessible API.

Living-memory is a production-ready persistent memory system implementing the Model Context Protocol (MCP). It enables AI models to maintain persistent memory across sessions through a sophisticated file system-based knowledge graph.