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An MCP server for intelligent logo extraction and processing, supporting automatic recognition and extraction of logo icons from website URLs, and providing image processing and vector conversion functions.

Provides AI assistants with expert-system analysis of hardware performance characteristics, GPU diagnostics, and LLM optimization recommendations. Built with TypeScript and published on npm as @yamaru-eu/hardware-probe, it evaluates system hardware in the context of large language model inference requirements. Useful for developers configuring AI workload deployments.

Production middleware for securing agentic AI systems. Enforces least-agency policy, scans for prompt injection, gates tool calls, and logs every decision to a tamper-evident SHA-256 chain. Evaluated against InjecAgent (1,054 cases), AgentDojo (949 cases), and memory poisoning (48 cases). Python + TypeScript SDKs.

This MCP server accelerates Medium article research by providing tools to extract article links from Medium archive pages, scrape full article content for summarization, and persistently store summaries with metadata using TinyDB. Built by Daniele Carta, it streamlines the workflow of discovering, processing, and organizing Medium articles by automating the extraction process and maintaining a local database of summaries with titles, URLs, tags, and timestamps. The implementation is particularly useful for content researchers, writers, and analysts who need to efficiently process and catalog multiple Medium articles for reference or analysis.

Agentizable: an open-source bounty network where AI agents post, fund, claim, solve, verify, and get paid for digital work.

Maps a company domain to its official social media URLs and follower counts across LinkedIn, X, Instagram, Facebook, and YouTube.

A read-only Reddit research server that exposes search, subreddit top posts, post details, and comment retrieval as typed tools with polite rate-limiting and citation lineage.

An MCP server that enables users to control Spotify playback, search music, and manage playlists through natural conversation. It is updated for the February 2026 Spotify Web API changes and supports full playlist CRUD operations.

Search and retrieve curated bookmarks from Raindrop.io directly in AI-powered IDEs, with features like component search and design system extraction.

Enables Claude Code to perform programmatic tool calling by executing Python scripts that interact with multiple MCP servers in a single round-trip. This reduces latency and token consumption by keeping intermediate tool results within the local Python runtime instead of the conversation context.

Provides read-only access to MySQL databases, enabling schema inspection, table listing, and execution of SELECT queries through the Model Context Protocol.

Connects AI agents to decentralized, community-built APIs on Solana, enabling autonomous discovery, payment, and execution of tools without subscriptions or API keys.

An MCP server that allows a planning agent to delegate tasks to executor agents (e.g., Claude Code, Aider) with bi-directional communication and real-time log streaming.

An MCP server that gives AI assistants persistent memory using an OpenAI vector store, enabling saving and semantic searching of text memories across sessions.

Enables secure search, tail, grep, and correlation of centrally collected infrastructure logs, turning blind restarts into informed remediation decisions.

MCP server that wraps the Brave Answers API, enabling synchronous Q&A and asynchronous deep research with job submission, status polling, and result retrieval.

Enables agents to delegate single-shot text completion and schema-validated structured data extraction to Mistral AI models over Streamable HTTP or stdio.

An MCP server that gives LLMs access to Garmin Connect data, including training, recovery, sleep, stress, VO2 Max, and running summaries for personalized fitness advice.

MCP server for spreadsheet files (.xlsx, .csv, .ods) - cell-level ops + DuckDB SQL engine.

This Python documentation MCP server, developed by an unnamed author, provides a tool for fetching Python documentation using the Brave Search API. Built with TypeScript and leveraging the Model Context Protocol SDK, it offers a streamlined interface for querying Python-related information. The implementation focuses on simplicity, offering a single 'get_python_docs' function that takes a search query and returns relevant documentation links. It's particularly useful for AI assistants or applications needing quick access to Python documentation, enabling tasks like code explanation, function lookup, or general Python language queries without requiring direct web scraping or complex API integrations.