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Fastcrw MCP Server

@us

基本情報

カテゴリ

ブラウザ自動化

ライセンス

AGPL-3.0

トランスポート

stdio

作者

us

投稿者

Recep Saritekin

Fastcrw MCP Server について

Fast, lightweight Firecrawl/Tavily alternative in Rust. Web scraper, crawler & search API with MCP server for AI agents. Drop-in Firecrawl-compatible API (/scrape, /crawl, /search). 2.3x faster than Tavily, 1.5x faster than Firecrawl in 1K-URL benchmarks. 6 MB RAM, single binary.

Fastcrw MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "crw": {
      "command": "npx",
      "args": [
        "crw-mcp"
      ],
      "env": {
        "CRW_API_KEY": "<YOUR_API_KEY>"
      }
    }
  }
}

Fastcrw MCP Server のツール

8

Scrape one URL to markdown, HTML, or links.

Start an async site crawl; returns a job id to poll with crw_check_crawl_status.

Poll an async crawl job and retrieve its pages.

Discover URLs on a site via sitemap and/or a short crawl. Returns a URL list only, no page content.

Extract structured JSON from URLs via a prompt and/or JSON schema. Async job — poll crw_check_extract_status with the returned id. Needs an LLM.

Poll an extract job; returns status and, when complete, a per-URL results array.

Request cancellation of an extract job. Returns the canonical status; cancelling remains non-terminal until the claimed URL settles.

Parse a local PDF (base64 in contentBase64) to markdown. No OCR: scanned PDFs return empty markdown with a warning.

概要

What is Fastcrw?

Fastcrw is a self-hosted, Rust-native web crawler and scraper designed for AI agents. It serves as an open-source alternative to Firecrawl, offering a single static binary with a native REST API under /v1/* (scrape, crawl, map, search, structured extraction, and change tracking) plus a /firecrawl/v2/* compatibility layer for migrating from Firecrawl. It can be self-hosted for free under AGPL-3.0 or used via the managed API at api.fastcrw.com.

How to use Fastcrw?

Use Fastcrw by running the self-hosted binary (e.g., docker run -p 3000:3000 ghcr.io/us/crw) and sending requests to its REST endpoints (/v1/scrape, /v1/crawl, etc.) with an API key. Alternatively, install the built-in MCP server via npm install -g crw-mcp for use with MCP-compatible AI agents like Claude Code, Cursor, or Windsurf.

Key features of Fastcrw

  • Single static binary (~8 MB), no Redis, Node.js, or Python required.
  • ~50 MB RAM idle, runs on a $5 VPS.
  • Native /v1/* API and Firecrawl v2 compatibility layer.
  • Change tracking with markdown git-diff and optional LLM judge.
  • AGPL-3.0 open core with managed commercial option.
  • Built-in MCP server and SDKs (npm, PyPI, Homebrew, Cargo).

Use cases of Fastcrw

  • AI agents scraping web content (markdown, HTML, JSON) programmatically.
  • Crawling multi-page documentation sites for knowledge base ingestion.
  • Mapping website link structures for sitemap generation or audit.
  • Structured JSON extraction from web pages using a JSON Schema.
  • Monitoring page changes with diff snapshots for alerting or tracking.

よくある質問

1

How does Fastcrw compare to Firecrawl?

Fastcrw is a Rust-native alternative that runs as a single static binary (~8 MB, ~50 MB RAM idle) compared to Firecrawl’s multi-container setup. It offers a `/firecrawl/v2/*` compatibility layer for easy migration and natively supports change tracking and MCP server integration.

2

What are the runtime dependencies?

None beyond the binary itself. There is no need for Redis, Node.js, Python, or a headless browser alongside the request path. Self-hosted search requires a SearXNG sidecar (via Docker Compose) if used.

3

Where does my data live?

Data stays entirely on your infrastructure when self-hosting (the binary runs locally). If using the managed API at `api.fastcrw.com`, data passes through their proxy network and dashboard.

4

What transports and authentication does Fastcrw support?

Transport is HTTP REST (TCP) with Bearer token authentication via `Authorization: Bearer <key>` header. The built-in MCP server uses the MCP protocol (stdio or SSE). Embedded mode runs in-process with no external transport.

5

Is there a usage limit for the self-hosted version?

The README does not specify hard limits. The memory baseline is ~50 MB idle, scaling with crawl queue size. The managed API offers 500 free credits on sign-up.

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