Latest MCP Servers

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.

A searchable collection of over 262 expert Claude configurations, MCP servers, agents, commands, hooks, and rules to boost Claude AI performance for specific tasks.

Enables AI assistants to interact with Anki for creating, editing, reviewing, and managing flashcards through a Model Context Protocol server.

Enables AI assistants to control Home Assistant devices through natural language commands, offering secure authentication, rate limiting, and high‑performance streaming via the Bun runtime.

Provides Django project exploration resources and a stateless shell, enabling LLM assistants to query apps, models, routes, settings and execute arbitrary Python code within a Django environment.

Manages GitHub projects with AI‑powered task generation, requirements traceability, and end‑to‑end workflow automation.

Provides a Model Context Protocol server that enables AI assistants to interact with the esa.io knowledge base, allowing reading, creating, updating, and managing posts, comments, tags, categories, and attachments via standardized tools.

Effortlessly create Model Context Protocol servers for exposing AI tools, resources, and prompts within NestJS applications.

Provides an MCP server that enables Claude Desktop to create, update, and manage Anki decks and cards via AnkiConnect.

Provides dynamic, reflective problem‑solving by tracking sequential thoughts and recommending MCP tools with confidence scores, rationale, and execution parameters.

Provides integration with Turso databases for LLMs, supporting organization‑level and database‑level operations through a two‑level authentication system.

Access authoritative Svelte 5 and SvelteKit definitions through a single, type‑safe tool that returns syntax, quick, or full documentation formats.

Provides unified access to multiple search engines, AI response tools, and content processing services through a single Model Context Protocol server.

Provides intelligent code indexing, search, and analysis for large language models to navigate codebases efficiently.

Provides IMAP and SMTP access through the MCP protocol, enabling AI agents to read and send emails.

Provides access to VS Code and Cursor local history through the Model Context Protocol, enabling AI assistants to retrieve, search, and restore file snapshots for data recovery and enhanced context awareness.

Packages GDAL‑style geospatial workflows with Python‑native libraries (Rasterio, GeoPandas, PyProj, etc.) and adds AI‑agent‑driven catalog discovery, metadata intelligence, and raster/vector processing backed by epistemic reasoning.