Reusable project context and specialist workflows for the AI tools you already use. AIWG places agents, skills, commands, and rules in provider-readable locations, with optional utilities for artifact memory, workflow orchestration, recovery, and discover

Context engineering for AI coding agents: product context, project missions, and 360 memory.

Find real products across 180+ Brazilian stores from chat context, with a ready-to-buy link.

x64dbg-MCP Server is a native MCP (Model Context Protocol) plugin for x64dbg that exposes the debugger's full functionality over HTTP. Connect any MCP-compatible AI assistant and control x64dbg programmatically: set breakpoints, step through code, read memory, dump registers, and more. Built with Zig — zero dependencies, single-binary output, cros

The context marketplace: expert guided journeys your assistant runs step by step.

A powerful multi-database server implementing the Model Context Protocol (MCP) to provide AI assistants with structured access to databases.

Workit Claude Code plugin — session and per-turn task context, branch policy on git shell commands, workit method skills, and verifier/reviewer/implementer agents

This is a 12306 ticket search server based on the Model Context Protocol (MCP).

Turn code into clarity. Generate accurate technical docs and AI-ready context in minutes—perfectly structured for human teams and intelligent agents.

Official data.gouv.fr Model Context Protocol (MCP) server that allows AI chatbots to search, explore, and analyze datasets from the French national Open Data platform, directly through conversation.

Your entire engineering context, deeply understood

Shared long-term memory for AI agents: save and recall context as a searchable knowledge graph.

🪐 🔧 Model Context Protocol (MCP) Server for Jupyter.

Enables AI assistants to read and write a local-first SQLite memory vault from inside a chat — orienting on inherited context, searching and fetching past decisions and notes, wandering linked memories, and recording new ones on demand. All data stays on the user's machine, shared across local and cloud tools via MCP.

Claw Orchestrator — run Claude Code, Codex, Antigravity, Grok Build, OpenCode, any ACP agent and custom coding CLIs as one unified runtime. Drop into Hermes Agent, Claude Desktop, Cursor, Cline, Continue, Zed, Windsurf, Goose or any Model Context Protocol

InnoShop is an AI-powered open source e-commerce system built on Laravel 13. It supports multiple AI models and native MCP (Model Context Protocol) for intelligent automation, with multi-language and multi-currency out of the box. Modular architecture and flexible plugin/theme system make it highly adaptable to diverse business needs.

A unified Model Context Protocol server implementation that aggregates multiple MCP servers into one.

An official Qdrant Model Context Protocol (MCP) server implementation

Stores what AI agents learn — thoughts, decisions, session events and repo facts — in PostgreSQL with pgvector and serves it back through versioned MCP tools with hybrid vector-plus-full-text retrieval and budgeted context packs. Enables multiple agents to share one scoped, role-isolated long-term memory, with deliberate promotion of distilled candidates into durable memories.

Enables Claude Code to delegate tasks to persistent GitHub Copilot CLI sessions via MCP, inspect pending tool requests, and approve each operation once or deny it while continuing multi-turn context. It bridges ACP runtime sessions locally over stdio without a public service or background daemon.

Enables AI applications to translate text through the Lara Translate API, with automatic language detection, context-aware translations, and custom instructions.

Enables MCP-compatible AI applications to translate text through the Lara Translate API, with automatic language detection, context-aware translations, and custom instructions.

Enables Claude and ChatGPT to manage Motion tasks through one shared API core, including capturing next actions, preserving resume context, checking duplicates, and reporting scheduling health. It serves local stdio clients and OAuth-protected Streamable HTTP clients.

Turns any OpenAPI spec into a single-tool MCP server where the model writes JavaScript against a typed api object in a QuickJS sandbox, so multi-step tasks run in one round trip and only the final result reaches context. Credentials, rate limiting, retries, write gating and audit logging stay on the host, outside the sandbox.