"How to use the terminal" matching MCP servers:

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Model-agnostic, agent-ready Obsidian MCP server with RBAC, SLSA provenance, and native search. 163 tools across 31 domains, multi-vault, pluggable embeddings.

Enables developers to index and search their own local PDF, DOCX, Markdown, and text documents from an MCP client or terminal, combining semantic similarity with keyword matching for exact technical terms. Everything runs on the user's machine with no API key, Docker, or external database, so private documents stay private and work offline after the initial model download.

Enables AI assistants to search a curated database of 200+ AI tool cards with pricing, platforms, use cases, and source links, so users can ask which tool to use for a task and get grounded recommendations.

Cross-model AI memory persistence server that gives every AI tool you use access to the same persistent memory.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Enables AI and LLM systems to interact with the Buttondown newsletter service, supporting email drafting, scheduling, analytics retrieval, and list management through a Model Context Protocol interface.

Provides OpenCode with adaptive long-term memory by storing preferences, lessons, and usage history locally in SQLite, enabling AI to remember and adapt to users through context-based learning.

Provides tools to fetch and search news from The Verge's RSS feed, allowing users to get today's news, retrieve random articles from the past week, and search for specific keywords in recent Verge content.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

Advanced content gap analysis using Query Decomposition and Keyword Fan-Out (Google's patented methodology). Tells you exactly what user queries your content covers - and what it misses. Built on academic research because I needed to understand how AI search engines actually evaluate content.

Enables integration with OpenAI models through the MCP protocol, supporting concise and detailed responses for use with Claude Desktop.

Enables Claude Desktop and other AI tools to interact directly with Figma, allowing for powerful AI-assisted design capabilities through natural language commands.

Allows the use of Kagi's API for web searching and content enrichment through methods like fastgpt, enrich/web, and enrich/news.