Latest MCP Servers

Enables LLMs to interact directly with Couchbase clusters, offering a suite of tools for cluster health, schema discovery, KV document operations, query execution, and performance analysis.

Compose AI agents, RAG pipelines, and MCP servers in a single declarative YAML file and run them locally, in containers, or in production without writing custom code.

Parse, view, query, edit, and export IFC, IDS, BCF, pointclouds and other AEC data directly in the browser, on a server, or in a desktop app, using a Rust‑based WASM core and WebGPU rendering.

Provides MCP endpoints that expose DeepSeek chat and reasoner models, supporting multi‑turn sessions, function calling, streaming, cost tracking, thinking mode, JSON output, and optional multimodal input.

Debug and analyze JavaScript code running in real Chrome pages, with persistent login state, zero script injection and layered anti‑detection, enabling AI coding assistants to perform genuine reverse‑engineering workflows.

Provides AI agents with a discovery layer to locate, evaluate, and install MCP servers from the Official Registry, Glama, and Smithery, delivering trust signals and ready‑to‑use configuration snippets.

Provides AI‑callable tools for football, Formula 1, and cricket, enabling Monte Carlo World Cup bracket simulations, pit‑stop strategy recommendations, and constraint‑based Dream11 fantasy‑team optimisation.

Enables Claude Desktop to browse Hacker News, retrieve story details, and read comments through a set of MCP tools, presenting clean‑formatted content for better readability.

Provides a professional Python framework that standardizes MCP server development, automatically converting FastAPI endpoints into AI-callable tools while supporting interface‑implementation separation and flexible dependency injection.

Generate a customized AI agent harness for any repository, complete with a repo‑aware CLI, MCP server, scoped memory, governance policies, and out‑of‑the‑box support for Claude Code, OpenAI Codex, pi.dev, Hermes, OpenClaw, and RVM.

Enables AI-driven generation, editing, verification, and simulation of mechanical designs using build123d/OpenCASCADE geometry and CalculiX analysis, while preserving editable parameters, stable topology pointers, and full provenance in a reproducible .aieng package.

Provides a Model Context Protocol server that exposes a rich set of dbt‑related tools—SQL execution, semantic‑layer queries, discovery APIs, dbt CLI commands, admin operations, code generation, lineage analysis, and product documentation retrieval—so AI agents can safely interact with dbt projects and platforms.

Provides CLI-based fuzz testing for MCP servers, covering tool arguments, protocol request types, and various transports while offering safety controls and detailed reporting.

Explore the Rijksmuseum’s artwork collections through AI‑driven conversation, using enriched metadata for semantic and full‑text search, provenance analysis, similarity comparisons, and spatial reasoning.

Provides remote access to a self‑hosted ChromaDB instance via MCP, letting Claude and other AI assistants share the same vector memory across desktop, mobile, and code environments.

Provides a Model Context Protocol server that lets Claude AI drive Dassault Systèmes CATIA V5 through natural‑language commands, exposing more than 50 CAD operations via COM automation.

Provides a Model Context Protocol server that enables natural‑language interaction with WordPress sites, exposing content, taxonomy, media, users, comments, plugins, and read‑only database queries as programmable tools.

Enables AI agents to search, read, and extract content from large PDFs without overflowing their context windows, supporting keyword and semantic search, OCR, table and image extraction, and correct reading order for multi‑column and CJK layouts.

A unified, production‑ready multi‑agent platform offering a Python SDK, CLI, Studio server, and desktop application, supporting meta‑agent orchestration, over 15 LLM providers, hierarchical memory, avatar/group chat, skill ecosystem, safety sandbox, and IM gateway.

Provides a persistent Model Context Protocol server that enables AI agents to conduct autonomous penetration testing on Linux distributions such as Kali and Parrot OS.

Offers a fully offline, searchable corpus of Apple’s developer documentation accessible through a command‑line interface, an MCP server, and a static website generator.

An open‑source server and CLI that lets AI agents design, slice, and drive a wide variety of 3D printers end‑to‑end, handling everything from model generation to final print without manual intervention.

A self‑hosted, single‑page dashboard that visualizes GPU usage, containers, systemd services, disks, and health across multiple hosts, with a built‑in read‑only MCP server enabling AI agents to query the same data.

Provides a semantic router that dynamically loads specialized agent personas, domain‑specific skills, and cognitive reasoning implants to fulfill user queries via any MCP‑compatible client.

Provides access to the DoiT API, enabling LLMs and other clients to retrieve cloud cost, incident, analytics, and management data for troubleshooting and analysis.

Connect AI assistants to WHOOP health and fitness data via a lightweight MCP server.

Provides a unified MCP server that lets AI agents read, write, and control Apple ecosystem apps and services through a rich set of native tools and safety primitives.

Deploy and manage any service on your own servers with one‑click deployment, GPU monitoring, AI model management, and native MCP integration.

Provides a local‑first searchable memory store that indexes Claude, Cursor, Cline, Telegram, Obsidian and other AI chat sessions into a single SQLite + FTS5 corpus, exposing the data to any MCP‑compatible client.

Scans installed AI agent components, MCP servers, and skill files for prompt‑injection, tool poisoning, toxic flows, hard‑coded secrets and other supply‑chain risks.

Provides a bridge to query multiple OpenAI‑compatible LLMs and CLI coding agents, offering a rubber‑duck debugging experience with multi‑duck consensus, debates, and structured tool access.

Enables AI models and MCP clients to seamlessly interact with Bugzilla instances, offering tools for retrieving bug details, history, comments, and performing write operations such as status updates, assignments, and commenting.