AI Agent Data Pipelines
Feed your AI agents live web data with structured extraction and multi-source research.
The Problem
AI agents reason well but are blind to live web data. Building custom scrapers for every data source is slow, fragile, and expensive to maintain. Agents need structured, real-time information to make accurate decisions.
The Solution
CrawlForge gives your agents direct access to web data through MCP. Use deep_research for multi-source analysis with conflict detection, and extract_content for clean, structured output -- no custom scrapers needed.
Code Example
// AI agent fetches and synthesizes live market data
const research = await mcp.deep_research({
query: "Latest funding rounds in AI infrastructure startups Q1 2026",
sources: 5,
conflict_detection: true,
});
// Extract structured data from a specific source
const content = await mcp.extract_content({
url: research.sources[0].url,
format: "markdown",
});
console.log(research.summary);
console.log(content.main_content);Tools Used
deep_research10 credits
extract_content2 credits
Estimated cost: ~12 credits per research task
Ready to Get Started?
Every new account gets 1,000 free credits. No credit card required.
Start Free with 1,000 CreditsRelated Use Cases
Real-Time Research Agents
Build AI agents that search the web, synthesize findings, and deliver up-to-date research.
deep_research (10 cr)search_web (3 cr)
AI Training Data Collection
Collect and structure large-scale web datasets for fine-tuning and training AI models.
batch_scrape (5 cr)extract_content (2 cr)