"Open source MCP (Model Context Protocol) implementations" matching MCP servers:

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.

A secure, local communication runtime bridge that interfaces a cloud-based Large Language Model (Claude Desktop) with a local machine execution environment using the Model Context Protocol (MCP).

Connects AI assistants to a Kali Linux terminal for executing security tools, managing interactive shell sessions, and performing penetration testing, CTF challenges, and security research tasks.

A Model Context Protocol (MCP) server that provides VSCode context and filesystem operations for AI assistants.

A local MCP server that delegates tasks to a subagent runtime via OpenAI-compatible interfaces, enabling file operations, command execution, and rollback of local file changes.

An MCP server for managing remote SSH servers, enabling AI agents to execute commands, transfer files, and perform deployment operations securely.

Provides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.

Operate packet-radio digipeater nodes from Claude and other MCP clients.

Enables ChatGPT's web interface to operate a real Mac by executing shell commands and reading or writing files over a reverse SSH tunnel, without installing a client or consuming API quota.

Project management CLI + MCP server for AI agents. Register projects once, open them anywhere, sync to S3, auto-init git, and wire into the hasna ecosystem.

An MCP Server that enables natural language interaction with the Open Policy Agent REST API, allowing users to manage policies, decisions, and data through conversational interfaces.

A server that manages conversation context for LLM interactions, storing recent prompts and providing relevant context for each user via REST API endpoints.

Enables AI agents to interact with real terminal sessions across local and remote hosts, driving multi-turn interactive programs like TUIs, REPLs, and SSH prompts through MCP.

Provides a controlled escape hatch for director-mode AI agents to run shell commands, write and edit files, execute Python code, supervise detached background jobs, acquire locks, and capture screenshots.

An MCP server that folds function and class implementations into structural skeletons while preserving signatures, interfaces, and docstrings, reducing tokens by up to 90%+ for AI agents. Exposes tools to get repository skeletons, unfold specific symbols on demand, and retrieve exact token and prompt cost savings metrics.

Studio MCP transforms any CLI command into an AI tool by using a simple template syntax to define input schemas and arguments. It enables AI agents like Claude and Cursor to execute local scripts and system commands through a dynamically generated Model Context Protocol server.

Enables AI assistants to execute AWS CLI commands and retrieve service documentation through the Model Context Protocol. It supports Unix pipes for output filtering and provides pre-defined prompt templates for common cloud management tasks.

Connects MCP-compatible AI clients and agents to one durable Project Brain plus controlled access to authorized project folders on your own machine. Enables file editing, terminal and Git operations, project intelligence, browser automation, and local MCP server federation, all scoped to explicit workspace grants.

A collection of Model Context Protocol implementations ranging from a minimal hello-world to an autonomous AI agent for software development.

An MCP (Model Context Protocol) server for debugging and interacting with SONiC (Software for Open Networking in the Cloud) network devices (DUTs).