The Problem
AI models have knowledge cutoff dates and cannot access current information. Research tasks that require up-to-the-minute data -- market trends, news, regulatory changes -- produce outdated or hallucinated answers.
Use Cases
Build AI agents that search the web, synthesize findings, and deliver up-to-date research. Every claim cites its source so answers stay verifiable.
Estimated cost: ~15 credits per research session
01Quick Answer
Connect CrawlForge over MCP so your agent can call search_web (5 credits) for live Google results and deep_research (10 credits) for multi-source analysis with conflict detection. It works from current data instead of a stale training cutoff, cutting outdated and hallucinated answers -- a typical research session runs about 10 to 15 credits.
02The brief
The Solution
CrawlForge deep_research performs multi-source research with automatic conflict detection, and search_web provides real-time Google results. Your agents always work with current data.
03In code
Code Example
real-time-research-agents.js
// Real-time research agent for market analysisconst search = await mcp.search_web({ query: "AI infrastructure market trends 2026", max_results: 10,}); // Deep research with conflict detection across sourcesconst research = await mcp.deep_research({ query: "Current state of AI infrastructure market, key players, and growth projections", sources: 8, conflict_detection: true, recency: "last_30_days",}); console.log(research.summary);console.log(`Sources: ${research.sources.length}`);console.log(`Conflicts found: ${research.conflicts.length}`);04The pipeline
Tools Used
15◆ credits
Estimated cost: ~15 credits per research session
- https://…
- 01deep_
research 10 credits - 02search_
web 5 credits - JSON · markdown
05Questions
Frequently Asked Questions
01How do I give an AI agent access to information past its training cutoff?
Connect CrawlForge over MCP so the agent can call search_web for live Google results and deep_research for multi-source analysis. It works from current data instead of a stale cutoff, which cuts down outdated or hallucinated answers.
02What does deep_research do that a plain search cannot?
deep_research runs a multi-stage process across several sources, synthesizes the findings, and flags conflicts between them, so the agent gets a verified summary rather than a list of links. search_web is the faster option when you only need current results.
03How much does a real-time research query cost?
deep_research is 10 credits and scales with the number of sources, and search_web is 5 credits. A typical research agent task lands around 10 to 15 credits, and the free 1,000-credit tier is enough to prototype an agent end to end.
04Can the research agent detect conflicting information?
Yes. deep_research includes conflict detection, so when sources disagree the agent surfaces the discrepancy instead of silently picking one. That is what makes it safer than single-source scraping for fact-sensitive tasks.
06Keep exploring
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