getagentictools MCP server

Search 41,000+ agent skills, MCP servers, Claude Code plugins, and agentic loops from inside any MCP-capable agent. This is the remote MCP server for getagentictools.com — real install counts and GitHub stars, refreshed weekly, never faked.

Endpoint: https://getagentictools.com/api/mcp — Streamable HTTP, free, no auth, no tracking.

Connect your client

Claude Code

claude mcp add --transport http getagentictools https://getagentictools.com/api/mcp

Cursor

// .cursor/mcp.json
{
  "mcpServers": {
    "getagentictools": { "url": "https://getagentictools.com/api/mcp" }
  }
}

VS Code (Copilot)

// .vscode/mcp.json
{
  "servers": {
    "getagentictools": { "type": "http", "url": "https://getagentictools.com/api/mcp" }
  }
}

OpenAI Codex

# ~/.codex/config.toml
[mcp_servers.getagentictools]
url = "https://getagentictools.com/api/mcp"

Gemini CLI

// ~/.gemini/settings.json
{
  "mcpServers": {
    "getagentictools": { "httpUrl": "https://getagentictools.com/api/mcp" }
  }
}

Then ask your agent things like “find me an MCP server for Postgres” or “what skills exist for PDF extraction?” — results carry install commands and links to their catalog pages.

Tools

How it works

• Deterministic. No LLM sits between your agent and the data — tokenized field-weighted scoring, popularity as a tiebreak only.
• Fresh by construction. The server reads the same dataset the website serves, generated in the same deploy, so it cannot drift from what you see on getagentictools.com. The catalog is re-harvested weekly from GitHub and public registries.
• Free and unauthenticated. Public data, read-only, no accounts, no tracking beyond standard web logs.

About this repo

This repo mirrors the deployed server source (api/), which lives in a private monorepo alongside the site and data pipeline. PRs are welcome — we port accepted changes upstream; direct pushes here are overwritten by the next sync.

The data endpoints it reads (/data/agent/*.json) are public — you can build your own tooling against them. Attribution appreciated.

License

MIT © Daniel Moka