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Cursor becomes dramatically more useful when you teach it exactly how to use your tools. A .cursorrules file tells Cursor which CrawlForge tools to pick for which tasks, how to optimize credit usage, and what patterns to follow when scraping.
This guide gives you production-ready Cursor rules for CrawlForge, plus the reasoning behind each rule so you can adapt them to your workflows.
Table of Contents
- What Are Cursor Rules?
- Prerequisites
- Step 1: Configure CrawlForge as an MCP Server
- Step 2: Create Your .cursorrules File
- Step 3: Web Research Rules
- Step 4: Data Extraction Rules
- Step 5: Credit Optimization Rules
- Step 6: Advanced Workflow Rules
- Complete .cursorrules Template
- Credit Cost Reference
- Next Steps
What Are Cursor Rules?
Cursor rules are project-scoped instructions that tell the Cursor AI assistant how to behave. They live in a .cursorrules file at your project root (or in .cursor/rules/ as individual files). When Cursor processes any request, it reads these rules as system-level context.
Without rules, Cursor will use CrawlForge tools but make suboptimal choices -- like using deep_research (10 credits) when fetch_url (1 credit) would suffice. Rules fix this by encoding your tool selection logic directly.
Prerequisites
- Cursor installed (v0.45+)
- CrawlForge MCP server installed:
npm install -g crawlforge-mcp-server - A CrawlForge API key (free tier: 1,000 credits)
Step 1: Configure CrawlForge as an MCP Server
Add CrawlForge to your Cursor MCP settings. Open Cursor Settings > MCP Servers and add:
{
"mcpServers": {
"crawlforge": {
"command": "crawlforge-mcp-server",
"env": {
"CRAWLFORGE_API_KEY": "cf_live_your_key_here"
}
}
}
}Restart Cursor. You should see CrawlForge listed under available MCP tools with all 20 tools accessible.
Step 2: Create Your .cursorrules File
Create .cursorrules at your project root:
// File: .cursorrules
// This file teaches Cursor how to use CrawlForge tools effectively.
// === CrawlForge MCP Tool Selection ===
// Always use the cheapest CrawlForge tool that accomplishes the task.
// Credit costs: fetch_url(1), extract_text(1), extract_links(1),
// extract_metadata(1), scrape_structured(2), extract_content(2),
// map_site(2), process_document(2), localization(2),
// track_changes(3), analyze_content(3),
// summarize_content(4), crawl_deep(4),
// search_web(5), batch_scrape(5),
// scrape_with_actions(5), stealth_mode(5), deep_research(10)Now let us build out each rule category.
Step 3: Web Research Rules
These rules teach Cursor when to search the web versus when to fetch a known URL directly:
## Web Research with CrawlForge
When I ask you to research a topic or find information online:
1. If I provide a specific URL, use `fetch_url` (1 credit) or `extract_content` (2 credits) -- NEVER use `search_web` for known URLs.
2. If I ask a general question requiring web search, use `search_web` (5 credits) with a focused query.
3. Only use `deep_research` (10 credits) when I explicitly ask for comprehensive multi-source research or when the topic requires cross-referencing multiple sources.
4. After fetching content, use `summarize_content` (2 credits) only if the content exceeds 2,000 words and I need a summary. Do not summarize short pages.
### URL-Known Pattern (1-2 credits)
- "Fetch the Stripe API docs" -> extract_content("https://docs.stripe.com/api")
- "What does this page say?" -> fetch_url(provided_url)
### Search Pattern (5 credits)
- "Find the best TypeScript testing frameworks" -> search_web("best TypeScript testing frameworks 2026")
- "What are competitors charging?" -> search_web("web scraping API pricing comparison")
### Deep Research Pattern (10 credits)
- "Do a comprehensive analysis of MCP adoption" -> deep_research("MCP protocol adoption trends")Step 4: Data Extraction Rules
Rules for selecting the right extraction tool based on what the user needs:
## Data Extraction with CrawlForge
When I ask you to extract data from websites:
1. For plain text content: use `extract_text` (1 credit)
2. For links/navigation: use `extract_links` (1 credit)
3. For page title, description, OG tags: use `extract_metadata` (1 credit)
4. For article content with readability: use `extract_content` (2 credits)
5. For specific elements via CSS selectors: use `scrape_structured` (2 credits)
6. For JavaScript-rendered pages or interactions: use `scrape_with_actions` (5 credits)
7. For anti-bot protected sites: try `fetch_url` first, then `stealth_mode` (5 credits) only if blocked
### Batch Operations
When I need data from 3+ URLs, always use `batch_scrape` (5 credits) instead of calling individual tools in a loop. batch_scrape handles concurrency and is more credit-efficient for bulk operations.
### CSS Selector Examples
When using scrape_structured, provide precise selectors:
- Product prices: `scrape_structured(url, {selectors: {price: ".price", name: "h1.product-title"}})`
- Article lists: `scrape_structured(url, {selectors: {titles: "article h2", links: "article a[href]"}})`Step 5: Credit Optimization Rules
These rules prevent Cursor from burning through credits unnecessarily:
## Credit Optimization Rules
1. NEVER call the same URL twice in one conversation. Cache the result and reference it.
2. Prefer 1-credit tools over 5-credit tools. The decision tree:
- Do I know the URL? -> fetch_url (1cr) NOT search_web (5cr)
- Do I need clean text? -> extract_text (1cr) NOT extract_content (2cr)
- Can I parse HTML locally? -> fetch_url (1cr) then parse the response
3. Before using scrape_with_actions, try fetch_url first. Many "JavaScript-rendered" pages actually serve content in the initial HTML.
4. Combine operations: fetch_url + local parsing is always cheaper than multiple specialized tool calls.
5. When asked about current credit balance, remind the user to check their dashboard at crawlforge.dev/dashboard.Step 6: Advanced Workflow Rules
Rules for complex, multi-step scraping workflows:
## Multi-Step Workflows
### Competitive Analysis Workflow
When asked to analyze competitors:
1. search_web to find competitor URLs (5 credits)
2. batch_scrape their pricing/feature pages (5 credits)
3. Present structured comparison table -- do NOT use deep_research unless explicitly asked
### Documentation Indexing Workflow
When asked to index documentation:
1. map_site to discover all doc pages (3 credits)
2. batch_scrape the discovered URLs (5 credits)
3. Store extracted content locally for RAG
### Content Monitoring Workflow
When asked to track website changes:
1. extract_content to capture current state (2 credits)
2. Store baseline locally
3. On subsequent checks, extract_content again and diff against baseline
### Site Audit Workflow
When asked to audit a website:
1. map_site for structure (3 credits)
2. extract_metadata on key pages for SEO data (1 credit each)
3. analyze_content on main pages for quality assessment (3 credits each)Complete .cursorrules Template
Here is the full, copy-paste-ready template combining all rules above:
# CrawlForge MCP Integration Rules
## Tool Selection Priority (cheapest first)
Always select the lowest-cost CrawlForge tool that accomplishes the task:
- 1 credit: fetch_url, extract_text, extract_links, extract_metadata
- 2 credits: scrape_structured, extract_content, map_site, process_document, localization
- 3 credits: track_changes, analyze_content
- 4 credits: summarize_content, crawl_deep
- 5 credits: search_web, batch_scrape, scrape_with_actions, stealth_mode
- 10 credits: deep_research (use ONLY when explicitly requested)
## Core Rules
1. Known URL -> fetch_url (1cr). NEVER search_web for a known URL.
2. 3+ URLs -> batch_scrape (5cr). NEVER loop individual calls.
3. Try fetch_url before scrape_with_actions. Most pages work without JS rendering.
4. Cache all results. Never fetch the same URL twice per conversation.
5. Only use deep_research when user explicitly asks for multi-source research.
## Output Formatting
- Present scraped data in markdown tables when comparing items
- Include source URLs as references
- Flag any pages that returned errors or empty contentCredit Cost Reference
| Credits | Tools | Typical Use Case |
|---|---|---|
| 1 | fetch_url, extract_text, extract_links, extract_metadata | Quick page fetching, link discovery |
| 2 | scrape_structured, extract_content, map_site, process_document, localization | Targeted data extraction, site mapping, document processing |
| 3 | track_changes, analyze_content | Change tracking, content analysis |
| 4 | summarize_content, crawl_deep | Summaries, multi-page crawling |
| 5 | search_web, batch_scrape, scrape_with_actions, stealth_mode | Web search, bulk operations, browser automation |
| 10 | deep_research | Comprehensive multi-source analysis |
Next Steps
- CrawlForge Quick Start -- install CrawlForge in 60 seconds
- Build a Research Assistant -- full project tutorial with Claude
- 20 Tools Reference -- complete tool documentation
- awesome-cursorrules on GitHub -- community Cursor rules collection
Start scraping smarter. Sign up free for 1,000 credits, install CrawlForge, and drop these rules into your .cursorrules file. Your Cursor AI will pick the right tool every time.