mcp-cloudflare-crawl

mcp-cloudflare-crawl

Enables LLMs to crawl websites via Cloudflare's Browser Rendering API, providing tools to start, monitor, cancel crawls, and retrieve structured content with AI extraction.

Category
访问服务器

README

mcp-cloudflare-crawl

An MCP server that exposes Cloudflare's Browser Rendering Crawl API as tools for LLM clients.

Requirements

  • uv
  • A Cloudflare account with Browser Rendering enabled
  • A Cloudflare API token with Browser Rendering - Edit permission

Setup

cp .env.example .env
# Edit .env and fill in your credentials

.env:

CLOUDFLARE_API_TOKEN=your_api_token_here
CLOUDFLARE_ACCOUNT_ID=your_account_id_here

Running

stdio (default — for Claude Desktop and most MCP clients)

uv run mcp-cloudflare-crawl

Streamable HTTP

uv run mcp-cloudflare-crawl --transport streamable-http
# Listens on http://127.0.0.1:8000/mcp by default

uv run mcp-cloudflare-crawl --transport streamable-http --host 0.0.0.0 --port 9000

Claude Code Integration

claude mcp add \
  --env CLOUDFLARE_API_TOKEN=your_api_token_here \
  --env CLOUDFLARE_ACCOUNT_ID=your_account_id_here \
  cloudflare-crawl \
  -- uv run --directory /absolute/path/to/mcp-cloudflare-crawl mcp-cloudflare-crawl

Add --scope user to make it available across all projects:

claude mcp add --scope user \
  --env CLOUDFLARE_API_TOKEN=your_api_token_here \
  --env CLOUDFLARE_ACCOUNT_ID=your_account_id_here \
  cloudflare-crawl \
  -- uv run --directory /absolute/path/to/mcp-cloudflare-crawl mcp-cloudflare-crawl

Claude Desktop Integration

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "cloudflare-crawl": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/absolute/path/to/mcp-cloudflare-crawl",
        "mcp-cloudflare-crawl"
      ],
      "env": {
        "CLOUDFLARE_API_TOKEN": "your_api_token_here",
        "CLOUDFLARE_ACCOUNT_ID": "your_account_id_here"
      }
    }
  }
}

Testing with curl

The server uses SSE (Server-Sent Events) format. Responses look like:

event: message
data: {"jsonrpc":"2.0","id":1,"result":{...}}

To parse with jq, extract the data: line first:

curl -s -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: $SESSION_ID" \
  -d '{...}' \
  | grep '^data:' | sed 's/^data: //' | jq .

Step 1 — Initialize session and capture session ID

SESSION_ID=$(curl -s -D - -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{
    "jsonrpc": "2.0", "id": 1, "method": "initialize",
    "params": {
      "protocolVersion": "2024-11-05",
      "capabilities": {},
      "clientInfo": {"name": "curl-test", "version": "1.0"}
    }
  }' | grep -i '^mcp-session-id:' | awk '{print $2}' | tr -d '\r')

echo "Session ID: $SESSION_ID"

Step 2 — List available tools

curl -s -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: $SESSION_ID" \
  -d '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}' \
  | grep '^data:' | sed 's/^data: //' | jq .

Step 3 — Start a crawl (all optional parameters)

curl -s -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: $SESSION_ID" \
  -d '{
    "jsonrpc": "2.0", "id": 3, "method": "tools/call",
    "params": {
      "name": "crawl_start",
      "arguments": {
        "url": "https://www.exampledocs.com/docs/",
        "crawl_purposes": ["search"],
        "limit": 50,
        "depth": 2,
        "formats": ["markdown"],
        "render": true,
        "max_age": 7200,
        "source": "all",
        "include_external_links": true,
        "include_subdomains": true,
        "include_patterns": ["**/api/v1/*"],
        "exclude_patterns": ["*/learning-paths/*"],
        "reject_resource_types": ["image", "media", "font"],
        "goto_options": {"waitUntil": "networkidle2", "timeout": 30000},
        "wait_for_selector": {"selector": "#content", "timeout": 5000}
      }
    }
  }' | grep '^data:' | sed 's/^data: //' | jq .

Step 4 — Poll status

curl -s -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: $SESSION_ID" \
  -d '{
    "jsonrpc": "2.0", "id": 4, "method": "tools/call",
    "params": {
      "name": "crawl_status",
      "arguments": {"job_id": "YOUR_JOB_ID"}
    }
  }' | grep '^data:' | sed 's/^data: //' | jq .

Step 5 — Crawl with AI structured extraction

Requires "json" in formats. Uses Cloudflare Workers AI and incurs additional charges.

curl -s -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: $SESSION_ID" \
  -d '{
    "jsonrpc": "2.0", "id": 5, "method": "tools/call",
    "params": {
      "name": "crawl_and_wait",
      "arguments": {
        "url": "https://example.com/",
        "formats": ["json"],
        "limit": 5,
        "json_options": {
          "prompt": "Extract product names and prices",
          "response_format": {"type": "object"}
        },
        "timeout": 120.0
      }
    }
  }' | grep '^data:' | sed 's/^data: //' | jq .

Step 6 — Crawl a password-protected site

curl -s -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: $SESSION_ID" \
  -d '{
    "jsonrpc": "2.0", "id": 6, "method": "tools/call",
    "params": {
      "name": "crawl_start",
      "arguments": {
        "url": "https://internal.example.com/docs/",
        "authenticate": {"username": "user", "password": "pass"},
        "extra_http_headers": {"X-API-Key": "abc123"},
        "cookies": [{"name": "session", "value": "xyz", "domain": "internal.example.com"}],
        "formats": ["markdown"]
      }
    }
  }' | grep '^data:' | sed 's/^data: //' | jq .

Step 7 — List all stored jobs

curl -s -X POST http://127.0.0.1:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "mcp-session-id: $SESSION_ID" \
  -d '{
    "jsonrpc": "2.0", "id": 7, "method": "tools/call",
    "params": {
      "name": "crawl_list",
      "arguments": {}
    }
  }' | grep '^data:' | sed 's/^data: //' | jq .

Tools

crawl_start

Submit a crawl job. Returns a job_id immediately — crawling happens asynchronously. The job is automatically saved to the local SQLite database.

Parameter Type Description
url string Required. Starting URL to crawl
limit int Max pages to crawl (default: 10, max: 100,000)
depth int Max link depth (default: 100,000)
source string URL discovery: "all", "sitemaps", or "links"
formats list[string] Output formats: "html", "markdown", "json"
render bool Execute JavaScript via headless browser (default: true)
max_age int Cache duration in seconds (default: 86400, max: 604800)
modified_since int Unix timestamp — only crawl pages modified since then
crawl_purposes list[string] Declare use: "search", "ai-input", "ai-train"
include_patterns list[string] URL patterns to include (* = no slash, ** = any)
exclude_patterns list[string] URL patterns to exclude (higher priority than include)
include_external_links bool Follow links to external domains
include_subdomains bool Follow links to subdomains
authenticate dict HTTP auth credentials: {"username": "...", "password": "..."}
extra_http_headers dict Custom request headers: {"X-API-Key": "..."}
json_options dict AI extraction config (requires "json" in formats). Keys: "prompt", "response_format", "custom_ai"
cookies list[dict] Browser cookies: [{"name": "...", "value": "...", "domain": "..."}]
goto_options dict Navigation behaviour: {"waitUntil": "networkidle2", "timeout": 30000}
wait_for_selector dict Wait for DOM element: {"selector": "#content", "timeout": 5000, "visible": true}
reject_resource_types list[string] Block resource types: "image", "media", "font", "stylesheet", "script"

Response:

{ "job_id": "c7f8s2d9-a8e7-4b6e-8e4d-3d4a1b2c3f4e" }

crawl_status

Poll the status and results of a crawl job. Also updates the job's status in the local database.

Parameter Type Description
job_id string Required. Job ID from crawl_start
cursor int Pagination token for large result sets (>10 MB)
limit int Records per page
status_filter string Filter by record status: queued, completed, disallowed, skipped, errored, cancelled

Response:

{
  "id": "c7f8s2d9-...",
  "status": "completed",
  "total": 20,
  "finished": 20,
  "browser_seconds_used": 134.7,
  "cursor": null,
  "records": [
    {
      "url": "https://example.com/",
      "status": "completed",
      "markdown": "# Example Domain\n...",
      "metadata": { "status": 200, "title": "Example Domain", "url": "https://example.com/" }
    }
  ]
}

Job statuses: running · completed · errored · cancelled_due_to_timeout · cancelled_due_to_limits · cancelled_by_user

Record statuses: queued · completed · errored · disallowed · skipped · cancelled


crawl_cancel

Cancel a running crawl job.

Parameter Type Description
job_id string Required. Job ID from crawl_start

crawl_and_wait

Start a crawl and block until it completes, returning the final results. Combines crawl_start and crawl_status polling in one call. The job is saved and status is updated in the local database throughout.

Accepts all parameters from crawl_start, plus:

Parameter Type Description
poll_interval float Seconds between status polls (default: 5.0)
timeout float Max seconds to wait (default: 300.0)

Use this for small crawls (a few pages). For large crawls, use crawl_start + crawl_status separately to avoid timeouts.


crawl_list

List all crawl jobs stored in the local SQLite database. Jobs are recorded automatically on crawl_start and crawl_and_wait, and their status is updated on every crawl_status or crawl_cancel call.

Parameter Type Description
status_filter string Filter by job status (see below)
limit int Max jobs to return (default: 50)
offset int Jobs to skip for pagination (default: 0)

Job statuses: submitted · running · completed · errored · cancelled_due_to_timeout · cancelled_due_to_limits · cancelled_by_user

Response:

{
  "jobs": [
    {
      "job_id": "c7f8s2d9-...",
      "url": "https://example.com/",
      "status": "completed",
      "created_at": "2026-03-25T00:00:00+00:00",
      "updated_at": "2026-03-25T00:01:00+00:00"
    }
  ],
  "count": 1
}

Job Database

Jobs are persisted in a local SQLite database across server restarts.

Default location: ~/.local/share/mcp-cloudflare-crawl/jobs.db

Override with environment variable:

MCP_DB_PATH=/path/to/custom/jobs.db

Development

# Install dependencies
uv sync

# Run tests
uv run pytest

# Run tests with verbose output
uv run pytest -v

Notes

  • The Cloudflare Crawl API is asynchronouscrawl_start returns immediately, results are retrieved via crawl_status.
  • The crawler respects robots.txt by default. Disallowed URLs appear with "status": "disallowed".
  • The json format uses Workers AI for structured extraction and incurs additional charges.
  • Setting render: false skips the headless browser and fetches static HTML — faster and currently unbilled during beta.
  • Results are retained for 14 days after a job completes. Maximum job runtime is 7 days.
  • The crawler identifies itself as CloudflareBrowserRenderingCrawler/1.0 and cannot bypass Cloudflare protection or CAPTCHAs.
  • HTTP 429 (rate limit) responses are automatically retried with exponential backoff (up to 3 retries: 1s → 2s → 4s). The Retry-After response header is respected when present.

License

MIT

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