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A standalone testing client and Apify Actor designed to connect to and test any MCP server using SSE transport.
Official Ruby implementation for MCP, enabling Ruby applications to function as MCP servers or clients.
A browser-based tool for visually inspecting and testing MCP servers, tools, and resources during development.
A central registry for discovering and sharing MCP servers across the community.
A collection of reference and maintained MCP server implementations for various data sources like GitHub, Slack, and Google Drive.
Provides the specification and SDK for the MCP Apps protocol, enabling embedded UIs within AI chat interfaces.
A tool for managing and installing MCP servers locally with one click for desktop AI applications.
Official Java implementation for MCP, integrated with Spring AI for building enterprise-grade MCP servers and clients.
Official Rust implementation for MCP, providing type-safe bindings for building servers and clients.
Official Kotlin implementation for MCP, developed with JetBrains for seamless use in JVM and Android environments.
Official Swift implementation for MCP, enabling AI tool integration for Apple platforms.
Official Go implementation for MCP, designed for building high-performance servers and integration with Google's ecosystem.
Official .NET implementation for MCP, enabling integration with C# applications and Microsoft's AI tools.
Official Python implementation for building MCP servers and clients, supporting both sync and async workflows.
Official TypeScript implementation providing base classes and transport layers for building MCP servers and clients.
Provides unified cloud infrastructure discovery tools, enabling agents to search for resources across multiple cloud providers.
A tool for AI developers and agents to find and insert relevant SVG icons into web projects using semantic search.
An official tool for searching and identifying existing MCP servers within the ecosystem, functioning as a discovery registry.
Enables AI assistants to search the web and fetch full-page content without an API key using the DuckDuckGo engine.
Enables AI assistants to retrieve legal and operational data for US businesses, including state filings and permits.
Provides a bridge to the Apify platform, allowing AI agents to run web scrapers and extract data from websites as MCP tools.
Enables AI assistants to manage and query Kubernetes and OpenShift clusters via MCP tools and resources.
Connects LLMs to the arXiv research repository, allowing users to search, summarize, and retrieve academic papers.
Provides tools for interacting with GitLab instances, supporting project management and CI/CD workflows for AI agents.
Acts as a gateway that transforms standard OpenAPI specifications into MCP tool definitions for dynamic tool discovery.
Provides AI-native search and crawling capabilities via MCP, designed for better context retrieval in LLM applications.
Official GitHub implementation of an MCP server for repository access, search, and issue management.
An opinionated development framework for building MCP servers with advanced features like UI widgets and better developer experience.
A community-maintained directory of MCP servers and resources, serving as a registry for discovery.
A directory focused on tools, SDKs, and infrastructure for the MCP ecosystem.
Provides privacy-focused web search capabilities to AI agents using the DuckDuckGo engine.
Allows AI assistants to access and modify personal knowledge bases in Obsidian via the Local REST API.
Exposes the Python Package Index (PyPI) to AI agents, enabling them to search for libraries and check dependency information.
Infrastructure that allows AI agents to discover and run complex multi-modal AI applications through a unified MCP interface.
A VS Code extension that functions as both an MCP client and inspector for testing tools, prompts, and resources.
An open-source AI assistant framework that integrates MCP to allow models to access local files and external tools.
Provides a standard set of authorization mechanisms and extensions for securing MCP server and client communication.
Contains official starter code and reference examples for building both MCP servers and clients.
An AI coding assistant for Neovim that supports MCP servers to provide enhanced context and tool capabilities to the user.
A Neovim plugin that acts as an MCP client, allowing users to interact with servers and tools directly within the editor.
A popular Pythonic framework for rapid MCP server development, providing decorators and automated schema generation.
Official PHP implementation for building MCP servers and clients, developed with the PHP Foundation.
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