Llm Tools AI Agent Skills

Self-improving tool discovery for AI agents. Install one MCP server. Your agent finds the rest. npm · GitHub · Contributing Forage is an MCP server that lets AI agents discover, install, and learn to use new tools — automatically. When an agent hits a wall, it forages for the right tool, installs it, and teaches itself how to use it. No restarts. No manual config. The agent gets permanently smarte

A Model Context Protocol (MCP) server implementation that integrates with Firecrawl for web scraping capabilities. - Web scraping, crawling, and discovery - Search and content extraction - Deep research and batch scraping - Cloud browser sessions with agent-browser automation - Automatic retries and rate limiting - Cloud and self-hosted support - SSE support Configuring Cursor 🖥️ Note: Requires C

🚨 No Nix/NixOS Required! Works on any system - Windows, macOS, Linux. You're just querying APIs. Your AI now has access to real NixOS data instead of making things up. You're welcome. An MCP server providing accurate, real-time information about: - NixOS packages - 130K+ packages that actually exist - NixOS options - 23K+ ways to configure your system - Home Manager - 5K+ options for dotfile enth

An MCP server that provides safe, read-only access to SQLite databases through Model Context Protocol (MCP). This server is built with the FastMCP framework, which enables LLMs to explore and query SQLite databases with built-in safety features and query validation. - Python 3.6+ - SQLite database file (path specified via environment variable) Install all required dependencies: - fastmcp: Framewor

Archive session learnings, debugging solutions, and deployment logs to .archive/yyyy-mm-dd/ as indexed markdown with searchable tags. Use when completing a significant task, resolving a tricky bug, deploying, or when the user says \"archive this\". Maintains .archive/MEMORY.md index for cross-session knowledge reuse.

This is a Model Context Protocol (MCP) server that integrates AgentQL's data extraction capabilities. - extract-web-data - extract structured data from a given 'url', using 'prompt' as a description of actual data and its fields to extract. To use AgentQL MCP Server to extract data from web pages, you need to install it via npm, get an API key from our Dev Portal, and configure it in your favorite

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. This document outlines the setup process and provides a basic example of using the client. Ingest anything from Slack, Discord, websites, Google Drive, email, Jira, Linear or GitHub into a Graphlit project - and then search and retrieve relevant knowledge within an MCP client like Cursor, Wind

A Model Context Protocol (MCP) server that provides local vector database functionality using FAISS for Retrieval-Augmented Generation (RAG) applications. - Local Vector Storage: Uses FAISS for efficient similarity search without external dependencies - Document Ingestion: Automatically chunks and embeds documents for storage - Semantic Search: Query documents using natural language with sentence