Browser Use

Web scraping and crawling via MCP for AI agents

Firecrawl MCP Server is the official MCP integration for Firecrawl, giving Cursor, Claude, Windsurf, and other MCP clients scrape, crawl, map, search, extract, and agent-style web research tools. It now supports a hosted remote endpoint, keyless rate-limited scrape/search/interact use, API-key/OAuth access for the full tool set, and self-hosted Firecrawl deployments.

Automate local Chrome browser via MCP

BrowserMCP is an MCP server that enables AI agents to automate a local Chrome browser — navigating pages, clicking elements, filling forms, extracting content, and taking screenshots. It gives coding agents the ability to interact with web applications the way a human would, directly from Claude Desktop, Cursor, or any MCP client.

Cloud browser automation via MCP for scalable testing

Browserbase MCP Server gives MCP clients a hosted or self-hostable browser through Browserbase and Stagehand. It exposes tools for starting sessions, navigating, acting, observing, extracting, and taking screenshots, with a hosted Streamable HTTP endpoint for easiest setup and local STDIO/Docker options for teams that want to run the Apache-licensed server themselves.

LLM-powered web scraping with graph-based extraction pipelines

ScrapeGraphAI is a Python library that uses LLMs and graph-based logic to build automated, self-healing web scraping pipelines. Developers describe desired data in natural language and ScrapeGraphAI constructs a processing graph that extracts structured information from any website. It supports multiple LLM providers, achieves 96%+ accuracy on semantic extraction benchmarks, and adapts to layout changes automatically. Over 20,000 GitHub stars.

Open-source AI agent framework with persistent memory, reusable skills, tools, and messaging gateways

Hermes Agent is an open-source AI agent framework with persistent memory, reusable skills, 40+ tools, cron jobs, and messaging gateways.

Open-source desktop AI coworker for browsing and code execution.

Accomplish Coworker is an MIT-licensed open-source AI coworker that runs on the desktop, combining computer-use style browsing with code execution so agents can research, implement, run, and debug workflows in one local environment.

Context compression for LLM apps and coding agents

Headroom is an Apache-2.0 context compression layer for LLM apps and coding agents. It compresses tool output, logs, files, RAG chunks, and agent history through a local library, proxy, wrapper, or MCP server, with retrieval hooks for bringing originals back when needed. Treat its savings numbers as Headroom-reported benchmarks, not independent aicoolies measurements.

Codebase knowledge graph MCP server for AI coding agents

Codebase Memory MCP is an MIT-licensed MCP server that turns a repository into a persistent code knowledge graph for AI coding agents. It gives Claude Code, Cursor, Codex-style agents, and other MCP clients structural queries for functions, classes, call chains, routes, and architecture, helping them explore large projects without repeatedly rereading files or relying only on broad search.

Python and TypeScript framework for production multi-agent systems

BeeAI Framework is an Apache-2.0 toolkit for building production-ready AI agents and multi-agent systems in Python and TypeScript. Its docs cover agents, tools, RAG, memory, workflows, backend providers, serving, and A2A/MCP integration surfaces, making it a vendor-neutral option for teams comparing LangGraph, CrewAI, Mastra, and related agent runtimes.

MCP integration platform for agent tool use at scale

Klavis AI is an Apache-2.0 MCP integration platform for teams connecting AI agents to external SaaS tools and APIs. The public repo and official docs position it as infrastructure for reliable tool access at scale, so it fits teams that want reusable MCP connectors without treating every integration as a one-off script or custom OAuth maintenance project.