io.github.us/crw

The open-source alternative to Firecrawl. One static binary, ~50 MB RAM idle, a native fastCRW REST API under /v1/* (scrape, crawl, map, search, structured extraction, and change tracking), plus a /firecrawl/v2/* Firecrawl compatibility layer for migrations, batch scrape, and PDF parse. Self-host free under AGPL-3.0, or hit our managed API at api.fastcrw.com. Reproducible 63.74% truth-recall on the public 1,000-URL dataset (diagnose_3way.py, 2026-05-08) — see fastcrw.com/benchmarks. Built in Rust because every millisecond of agent latency compounds.

Works with: Claude Code · Cursor · Windsurf · Cline · Copilot · Continue.dev · Codex · Gemini CLI

Why fastCRW?

• Rust-native, single static binary — no Redis, no Node.js, no Python venv, no headless-browser sidecar in the request path. One binary, one config file, one process.
• ~50 MB RAM idle — leaves headroom on a $5 VPS. Browser-render-first stacks (Firecrawl, Crawl4AI) carry a Chromium heap baseline measured in hundreds of MB before a single request lands.
• Native /v1, compatibility /firecrawl/v2 — new fastCRW projects should use /v1/scrape, /v1/crawl, /v1/map, and /v1/search. Existing Firecrawl v2 SDK projects can use the /firecrawl/v2/* compatibility layer (FirecrawlApp(api_url="https://api.fastcrw.com")) and validate the documented differences before switching production traffic.
• Change tracking & monitoring — diff a page against a prior snapshot (markdown git-diff, per-field JSON, or both) with an optional LLM "meaningful-change" judge. Stateless changeTracking primitive in the engine; scheduled monitors + signed-webhook/email alerts on the managed platform. See the Monitoring docs.
• AGPL-3.0 open core + managed option — self-host free, or point at api.fastcrw.com for managed proxy network, dashboard, and SLA without the AGPL obligations on your application code.

Comparison Table

Qualitative positioning vs. the two most-cited alternatives — the same two in the reproducible benchmark below. Numerical claims trace to the inline sources noted; everything else is descriptive.

Pricing/spec cells where claimed link to the vendor page; everything else is the qualitative architectural shape, not a comparison number.

Quickstart

Hit the managed API at api.fastcrw.com, or self-host the same binary.

# /v1/scrape — URL → markdown / HTML / JSON / links
curl -X POST https://api.fastcrw.com/v1/scrape \
  -H "Authorization: Bearer $CRW_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://example.com","formats":["markdown"]}'

# /v1/scrape + formats:["json"] — structured JSON extraction via a JSON Schema
curl -X POST https://api.fastcrw.com/v1/scrape \
  -H "Authorization: Bearer $CRW_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url":"https://example.com",
    "formats":["json"],
    "jsonSchema":{
      "type":"object",
      "properties":{"title":{"type":"string"}}
    }
  }'

# /v1/crawl — async multi-page job (returns a job id; poll with /v1/crawl/:id)
curl -X POST https://api.fastcrw.com/v1/crawl \
  -H "Authorization: Bearer $CRW_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://docs.example.com","maxDepth":2,"maxPages":50}'

# Self-host (no auth, localhost) — single docker command
docker run -p 3000:3000 ghcr.io/us/crw
curl http://localhost:3000/v1/scrape \
  -H "Content-Type: application/json" \
  -d '{"url":"https://example.com"}'

Other install paths (each documented under Install further down):

npx crw-mcp                           # zero install — runs the embedded engine
pip install crw                        # Python SDK (auto-downloads binary)
brew install us/crw/crw                # Homebrew
cargo install crw-cli                  # Cargo
curl -fsSL https://fastcrw.com/install | sh

Why Rust?

Cold start is sub-second and the resident memory ceiling is bounded by the crawl queue, not by a JavaScript runtime or a headless browser parked in the background. An agent that issues N scrapes per task pays the network floor N times — anything you add on top (process spawn, JIT warmup, browser navigation overhead) multiplies. Pushing the request-path language down to Rust strips that surcharge out of every call. The same property lets one static binary saturate a $5 VPS instead of needing a multi-container compose stack, which is why the idle footprint is in the tens of MB rather than the hundreds.

MCP + SDK quickstart

fastCRW ships a built-in MCP server so any MCP-compatible agent (Claude Code, Cursor, Windsurf, Cline, Continue.dev, Codex, Gemini CLI) can call scraping tools without bespoke glue. Embedded mode runs the engine in-process — no server, no API key, no setup. The crw Python SDK and the crw-mcp Node binary both shell to the same Rust core.

npm install -g crw-mcp          # MCP server (Node wrapper)
pip install crw                 # Python SDK (auto-downloads binary)
claude mcp add crw -- npx -y crw-mcp                                       # Claude Code, embedded
claude mcp add crw \
  -e CRW_API_URL=https://api.fastcrw.com -e CRW_API_KEY=… \
  -- npx -y crw-mcp                                                        # Claude Code, managed

Per-client config recipes (Claude Desktop, Cursor, Windsurf, Cline, Continue.dev) live under docs.fastcrw.com/mcp-clients/.

Agent Skills

Beyond raw MCP tools, fastCRW ships a set of agent skills — reusable instruction packs that teach AI coding agents when and how to scrape, crawl, map, search, parse, extract, and change-track the web. Install into any agent (Claude Code, Codex, Cursor, OpenCode, Gemini CLI, Windsurf + more) with one command:

npx skills add us/crw                 # all 12 skills, into every detected agent
npx skills add us/crw@crw-scrape      # just one
npx skills add -g us/crw              # global (user-level)

The skills drive the crw CLI, the crw-mcp tools, or the REST API — pick whatever surface you have. No API key needed for self-hosted search (SearXNG). Full catalog and per-skill docs: skills/. Also packaged as a plugin marketplace for Claude Code, Codex, and Cursor (.claude-plugin/, .codex-plugin/, .cursor-plugin/).

Self-host vs Managed

The binary is the same in both modes — you can develop against your self-hosted instance and ship to managed without code changes.

Install

MCP server (crw-mcp) — recommended for AI agents

npx crw-mcp                              # zero install (npm)
pip install crw                          # Python SDK (auto-downloads binary)
brew install us/crw/crw-mcp              # Homebrew
cargo install crw-mcp                    # Cargo (full embedded, ~17 MB)
docker run -i ghcr.io/us/crw crw-mcp     # Docker

Lean browser-free proxy build (~4.2 MB, no headless browser engine — proxy/cloud mode only):

cargo build --profile release-small --no-default-features -p crw-mcp

CLI (crw) — scrape URLs from your terminal

brew install us/crw/crw

# One-line install (auto-detects OS & arch):
curl -fsSL https://fastcrw.com/install | CRW_BINARY=crw sh

# APT (Debian/Ubuntu):
curl -fsSL https://apt.fastcrw.com/gpg.key | sudo gpg --dearmor -o /usr/share/keyrings/crw.gpg
echo "deb [signed-by=/usr/share/keyrings/crw.gpg] https://apt.fastcrw.com stable main" \
  | sudo tee /etc/apt/sources.list.d/crw.list
sudo apt update && sudo apt install crw

cargo install crw-cli

API server (crw-server) — native REST API plus Firecrawl compatibility

For serving multiple apps, other languages (Node.js, Go, Java), or as a shared microservice.

brew install us/crw/crw-server

# One-line install:
curl -fsSL https://fastcrw.com/install | CRW_BINARY=crw-server sh

# Docker:
docker run -p 3000:3000 ghcr.io/us/crw

Docker Compose ships with lightpanda by default; chrome is opt-in:

docker compose up -d                                         # http + lightpanda
docker compose --profile heavy up -d                         # + chrome failover
docker compose -f docker-compose.yml \
  -f docker-compose.stealth.yml --profile stealth up -d      # browserless stealth tier

There's also an optional Camoufox stealth tier (REST sidecar, opt-in) for fingerprint-blocked targets the CDP renderers can't pass — off by default and never touches the auto chain unless you turn it on. Build with --features camoufox; see JS rendering → Camoufox.

See the self-hosting guide for production hardening, auth, reverse proxy, and resource tuning.

API endpoints

Firecrawl v2 compatibility surface — scrape, crawl, map, and search are also served under /firecrawl/v2/* with Firecrawl v2 request/response shapes, plus compatibility-only POST /firecrawl/v2/batch/scrape, POST /firecrawl/v2/parse (PDF → markdown), and GET /firecrawl/v2/crawl/active. Use this when migrating existing Firecrawl v2 SDK code; new fastCRW integrations should start with /v1.

Full reference at docs.fastcrw.com/#rest-api. The Firecrawl compatibility matrix (field-by-field diff) lives in COMPATIBILITY-firecrawl.md.

Benchmark

Reproduce it yourself first — the canonical harness is diagnose_3way.py (matches truth text against md + strip_md_links(md), applied identically to all three tools — a fairness control, not a looser number):

cd ~/coding/crw/crw-opencore
docker compose -f docker-compose.yml -f docker-compose.override.yml \
               -f docker-compose.stealth.yml --profile stealth up -d
docker start crawl4ai-bench
cd ~/coding/crw/competitors/firecrawl && docker compose up -d

cd ~/coding/crw/crw-opencore
uv run python bench/diagnose_3way.py \
  --max-urls 1000 --tools crw,crawl4ai,firecrawl \
  --concurrency 5 --timeout 120 \
  --out bench/server-runs/diag3w-1000-full.jsonl

3-way scrape benchmark, full 1,000-URL run on Firecrawl's scrape-content-dataset-v1 (diagnose_3way.py, 2026-05-08, concurrency 5, timeout 120s):

fastCRW leads on every axis — top truth-recall, fastest median, and the lowest p90 tail — with 0 thrown errors across all 3,000 requests, and it uniquely recovers 34 URLs the other two miss (70% more than crawl4ai and Firecrawl combined). The 63.74% denominator is 819 labeled/matchable URLs, not 3,000 requests, not 1,000.

Two tunable modes, one engine, one config toggle. Recall mode (the full ladder) maximizes truth-recall, recovering the long tail of hard pages the others miss. Fast mode (LightPanda-only, no Chrome tier) optimizes the latency tail — p90 4348 ms, the lowest of the three (diagnose_3way.py, N=1000). Same binary, same API; pick accuracy or latency per workload.

Full result of record: bench/server-runs/RESULT_3WAY_1000_FULL.md.

SDKs and integrations

Python

pip install crw

from crw import CrwClient

# Managed (includes web search):
client = CrwClient(api_url="https://api.fastcrw.com", api_key="YOUR_API_KEY")
# Local (embedded, no server needed):
# client = CrwClient()

result = client.scrape("https://example.com", formats=["markdown", "links"])
pages = client.crawl("https://docs.example.com", max_depth=2, max_pages=50)
urls = client.map("https://example.com")
results = client.search("AI news", limit=10, sources=["web", "news"])

Requires Python 3.10+. Local mode auto-downloads crw-mcp on first use.

Framework extras:

pip install crw[crewai]    # CRW scraping tools for CrewAI agents
pip install crw[langchain] # CRW document loader for LangChain

TypeScript / Node.js

npm install crw-sdk

SDK examples →

Frameworks & platforms

CrewAI · LangChain · Agno · Dify · n8n · Flowise

All integrations →

Architecture

┌─────────────────────────────────────────────┐
│                 crw-server                  │
│         Axum HTTP API + Auth + MCP          │
├──────────┬──────────┬───────────────────────┤
│ crw-crawl│crw-extract│    crw-renderer      │
│ BFS crawl│ HTML→MD   │  HTTP + CDP(WS)      │
│ robots   │ LLM/JSON  │  LightPanda/Chrome   │
│ sitemap  │ clean/read│  auto-detect SPA     │
├──────────┴──────────┴───────────────────────┤
│                 crw-core                    │
│        Types, Config, Errors                │
└─────────────────────────────────────────────┘

Full architecture docs →

Security

• SSRF protection — blocks loopback, private IPs, cloud metadata (169.254.x.x), IPv6 mapped addresses, and non-HTTP schemes (file://, data:)
• Auth — optional Bearer token with constant-time comparison
• robots.txt — RFC 9309 compliant with wildcard patterns
• Rate limiting — token-bucket algorithm, returns 429 with error_code
• Resource limits — max body 1 MB, max crawl depth 10, max pages 1,000

Full security docs →

Contributing

Contributions are welcome — issues and PRs both.

1. Fork the repository
2. Install pre-commit hooks: make hooks
3. Create your feature branch (git checkout -b feat/my-feature)
4. Commit your changes (git commit -m 'feat: add my feature')
5. Push to the branch (git push origin feat/my-feature)
6. Open a Pull Request

The pre-commit hook runs the same checks as CI (cargo fmt, cargo clippy, cargo test). Run manually with make check.

Contributors

License

fastCRW is open source under AGPL-3.0. If you embed fastCRW in a closed-source product or expose it as a hosted service to third parties and you can't comply with AGPL's source-availability requirements, the managed offering at fastcrw.com includes a commercial carve-out, and standalone commercial licenses are available on request — write to hello@fastcrw.com.

Links

• Documentation: docs.fastcrw.com
• API reference: docs.fastcrw.com/#rest-api
• MCP setup guide: docs.fastcrw.com/#mcp
• Playground: docs.fastcrw.com/playground/
• Benchmarks: fastcrw.com/benchmarks
• Marketing site: fastcrw.com
• Changelog: CHANGELOG.md
• X / Twitter: @fast_crw
• LinkedIn: fastcrw
• Discord: discord.gg/kkFh2SC8
• MCP Registry: registry.modelcontextprotocol.io

Star History

It is the sole responsibility of end users to respect websites' policies when scraping. Users are advised to adhere to applicable privacy policies and terms of use. By default, fastCRW respects robots.txt directives.