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Enables planning, scaffolding, diagnosing, and hardening MediaSFU frontend and backend integrations across multiple SDKs with 138 integration tools.

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.

An MCP server that gives AI assistants direct access to NASA's Exoplanet Archive — the authoritative database of every confirmed exoplanet, candidate planet, and host star.

Transforms a Medium article archive into an intelligent writing assistant for book writing, enabling content analysis, theme extraction, and chapter organization.

MCP server for space weather and HF propagation conditions — live solar flux, Kp index, DSCOVR solar wind, X-ray flux, alerts, 27-day forecast, and band-by-band outlook through any MCP-compatible AI assistant.

Todoist MCP Pack

An AI-powered research agent that autonomously searches the web, reads PDFs, and synthesises findings into structured Markdown reports. Built as a portfolio project demonstrating MCP protocol, agentic AI systems, and cloud deployment on AWS.

Exposes the official lark-cli as an MCP server, enabling agents to execute arbitrary CLI commands, query API schemas, and manage authentication.

A command-line chat interface that connects to an MCP server for reading and editing documents. It provides tools for document manipulation, resource access, and prompts for formatting and summarization.

An MCP server for EMBA firmware analysis that exposes structured security findings and tools to LLMs. It enables users to programmatically query, reason over, and correlate firmware analysis results such as kernel details, SBOMs, and attack paths.

MCP server that exposes APRS-IS network tools to LLM agents, enabling sending APRS messages, querying positions, finding nearby stations, and listening to live packet streams.

Enables task management through natural language commands in English or Spanish. Supports creating, listing, updating, completing, and deleting tasks with local SQLite storage.

An MCP server for Obsidian that enables canvas creation with auto-layout, BM25-ranked search, vault theme mapping, and 27 tools for managing notes, files, and links.

Connects AI coding environments to the VibeFix bug bounty marketplace. Developers can browse and filter open bounties by category, platform, and difficulty, view detailed bounty information, check personal profiles and submissions, and apply to private bounties. Customers can post new bounties, manage existing ones, review submissions, and accept winning fixes. Includes diagnostic tools for running Lighthouse audits and JavaScript error scanning on target URLs. Requires an API key from the VibeFix dashboard for authentication.

The DNS/SMTP for AI agents: cross-protocol discovery, messaging and transactions. No middleman fees.

Enables Claude Code to directly access NinjaTrader 8 accounts, positions, orders, market data, charts, and strategy management through a NinjaScript Add-On.

Enables storing and retrieving text in a local vector store using Qdrant, running fully locally with no external database or API key.

This MCP server implementation provides a simple sleep/wait tool, allowing AI agents to introduce delays between operations. Developed by Garoth, it offers a single 'sleep' tool that waits for a specified duration in milliseconds. Built with TypeScript and integrating the Model Context Protocol SDK, the server focuses on ease of use and configuration. It is particularly useful for scenarios requiring timed delays, such as spacing out API calls, testing eventually consistent systems, or simulating time-dependent processes. The implementation includes Jest-based tests to verify sleep functionality with various durations and supports easy deployment through npm scripts.

This MCP server provides local Medusa.js documentation access through fuzzy search capabilities using Fuse.js for semantic text matching and section-based content retrieval. Built with TypeScript and the Model Context Protocol SDK, it parses documentation files into searchable sections with configurable search thresholds and result limits, offering three core tools: semantic search across documentation content, specific section retrieval by title or path, and comprehensive section listing with optional category filtering. The implementation features flexible file path resolution with multiple fallback locations, markdown-based section parsing that handles nested headers, and configurable preview lengths for search results, making it ideal for developers working with Medusa.js who need quick access to framework documentation without leaving their development environment or AI assistant workflow.

Enables LLMs to query and retrieve data from Burp Suite proxy history using SQL-like syntax, aiding security researchers in efficient analysis.