Latest MCP Servers

Provides a knowledge‑graph memory server backed by DuckDB, enabling fast, scalable storage, fuzzy search, and relational queries over entities, observations, and relations.

Provides a secure, unified endpoint for routing all MCP traffic, enforcing RBAC, policies, and full observability while supporting deployment on Docker, Kubernetes, Bun, or Node.

Provides persistent memory, semantic code search, and graph‑based analysis for AI tools through an MCP server.

Provides intelligent semantic code search for AI assistants by indexing codebases with local AI model embeddings and exposing searchable context through the Model Context Protocol.

Automates X/Twitter tasks such as profile scraping, follower management, tweet searching, liking, retweeting, posting, and multi‑account actions through a CLI, browser console scripts, Node.js API, and an MCP server for AI agents, all without requiring Twitter API keys or fees.

Provides fast, local‑first code indexing and search across dozens of programming languages, enabling LLMs and developers to retrieve symbols, definitions, and code snippets with sub‑100 ms latency.

Enables AI assistants to query PortOne's developer and help center documentation, retrieve channel lists, add test channels, view sub‑store information, and obtain payment histories through the Model Context Protocol.

Provides an extensible platform for AI‑augmented document ingestion, hybrid (vector + full‑text + graph) retrieval, automatic knowledge‑graph construction, and conversational query answering, with front‑ends in React, Angular, and Vue and a FastAPI‑based backend.

Provides AI‑enhanced analysis of NPM packages, delivering version history, dependency mapping, security vulnerability scanning, size metrics, and quality scores through the Model Context Protocol.

Unifies ACK cluster management, native Kubernetes operations, observability, security audit and diagnostic capabilities into a single AI‑native toolset, allowing natural‑language interaction with AI assistants to perform complex container‑oriented AIOps tasks.

Provides comprehensive web performance, accessibility, SEO, and security audits using Google Lighthouse, enabling AI agents to evaluate and improve websites.

Provides a set of AI‑friendly tools for creating, reading, updating and deleting Backlog resources such as projects, issues, wiki pages, Git repositories and notifications, with optional response optimization and token limiting.

Orchestrates a network of asynchronous agents and streaming swarms to conduct ensemble‑consensus research, automatically creating indexed PGlite databases in WebAssembly and providing semantic, hybrid, and SQL search capabilities.

Provides real-time access to shadcn-svelte component documentation and developer utilities via web scraping, exposed through an MCP server with HTTP and SSE transports.

Provides AI agents instant access to Apple developer documentation through semantic, keyword, and hybrid retrieval‑augmented generation (RAG) techniques.

A unified AI development platform that provides a TypeScript SDK and professional CLI to build, test, and deploy applications across multiple AI providers, with built‑in tools, MCP integration, and enterprise‑grade features such as Redis conversation memory, cost optimization, and multi‑provider failover.

Provides a unified enterprise gateway and registry for discovering, securing, and executing Model Context Protocol (MCP) tools via a standardized HTTP API with sandboxing and OAuth 2.1 support.

Enables AI assistants such as Claude to retrieve, create, review, and upload content in microCMS via a Model Context Protocol server.

Provides programmatic access for AI assistants to query and manage Prometheus Alertmanager resources, supporting authentication, multi‑tenant handling, and pagination to fit LLM context limits.

Provides a production‑ready foundation for building custom Model Context Protocol servers in TypeScript, featuring IP geolocation tools, a full CLI, dual STDIO/HTTP transports, TOON output format, JMESPath filtering, and an extensible 5‑layer architecture.

Enables AI applications and tools to connect to MCP servers on AWS using AWS IAM (SigV4) authentication, handling request signing automatically and providing both a command‑line proxy and a Python library.

Enables analysts to converse with OpenCTI using natural language through Claude Desktop, turning plain‑English questions into instant, context‑rich threat‑intelligence answers.

Provides a security‑first MCP server that enables AI agents to orchestrate Ghidra, Radare2, and YARA for fully automated reverse‑engineering and malware‑analysis workflows.

Enables AI assistants to interact with testing and monitoring tools via natural‑language queries, offering access to error monitoring, test management, API documentation, contract testing, and code review capabilities.

Scalable multi‑language code analysis framework built on Tree‑sitter, operable through a command‑line interface or as an MCP server for AI assistants.

Transforms natural language prompts into executable discrete-event and system dynamics simulation models, enabling LLMs to create, validate, and run simulations via a Model Context Protocol server.

Enables natural language interaction with Tableau data through AI-driven queries, supporting both Tableau Server and Tableau Cloud environments.

Install, manage, and run MCP servers in isolated containers, automatically configure popular AI coding assistants, and connect them to AI agents through a unified UI and CLI.

Provides an interactive UI popup for user input, file and image attachment, and emits a structured tag‑based output that AI agents can consume directly.

A comprehensive collection of Model Context Protocol (MCP) servers that expose Volcengine cloud resources and third‑party services through natural‑language interfaces, enabling AI‑driven operations across compute, storage, databases, networking, security, and developer utilities.