The Universal Context Layer
for AI Coding Agents.
UseAgents gives agents a single MCP-powered registry of tools, install steps, and docs so they stop guessing, stop hallucinating, and always pick the right library instantly.
Plug Into Any Agentic Coding Environment.
Features
Built for agents: concise, structured, and install-ready so they pick the right tool and act without hesitation.
Curated registry
250+ vetted tools with accurate names, slugs, tags, and install commands.
MCP-native responses
Structured output formatted for agents—no scraping, no guesswork.
Install-first answers
Surface the exact install steps so agents act immediately, not after digging through docs.
Freshness focus
Designed to stay current with tool updates so agents stop hallucinating outdated packages.
Why Agents Need This
Agents hallucinate because the world they operate in is chaotic, with tools shifting, libraries forking, and documentation drifting out of sync, leaving them to guess. They don’t need bigger brains; they need solid ground. UseAgents provides that ground with a reliable, always-current registry of tools, libraries, install commands, and documentation so agents choose the right tool every time.
How It Works
The agent asks for a tool.
Your coding agent needs something — a CLI, a library, an SDK, an API. Instead of guessing or scraping outdated docs, it sends a structured MCP request asking UseAgents what exists.
UseAgents provides the correct context instantly.
UseAgents looks through its unified registry of tools, metadata, install steps, tags, and docs. It returns a clean, machine-readable response so the agent always knows the right thing to install or call.
The agent builds without hallucinating.
Armed with accurate context, the agent installs the correct library, uses the right commands, and generates working code on the first try — no guessing, no stale docs, no web search chaos.
Right now, every AI coding agent guesses its tools from old training data. Even with web access, the search space is huge. UseAgents creates a stable context layer so agents stop hallucinating and start building.