Give Your AI Agents
Live Web Access
An agent that can't read the web is guessing. DataBlue ships a native MCP server plus a clean REST API, so Claude, Cursor, and your own agents can search the web and scrape any page into LLM-ready data — as a tool call, with no glue code or proxy plumbing.
Web Tools Agents Actually Use.
Native MCP Server
Point any MCP-compatible client — Claude Desktop, Cursor, your own runtime — at DataBlue and your agent instantly gains search, scrape, crawl, and extract tools. No custom integration layer to build or maintain.
Structured, Token-Lean Output
Agents pay for every token they read. DataBlue returns clean markdown and typed JSON instead of raw HTML, so context windows stay focused on signal — not nav bars, scripts, and boilerplate.
Search + Scrape in One Tool Belt
Discovery and extraction live behind the same API key. An agent can search the web, pick a result, and read the full page in a single reasoning loop — exactly the pattern tool-using LLMs are built for.
Reliable Under Autonomy
Agents retry, branch, and run unattended. High concurrency, JavaScript rendering, and non-expiring credits mean your agent keeps working at 3am without tripping rate limits or burning a monthly quota.
Add DataBlue as an MCP Server.
Drop this into your MCP client config and your agent gains web search and scraping tools on the next restart. That's the whole integration.
{
"mcpServers": {
"datablue": {
"command": "npx",
"args": ["-y", "@datablue/mcp"],
"env": {
"DATABLUE_API_KEY": "<your-key>"
}
}
}
}
// Your agent can now call:
// search(query) -> live web results
// scrape(url) -> page as markdown / JSON
// crawl(url) -> whole-site extraction
// extract(url, schema) -> structured fieldsFrom Config to Web-Aware Agent.
Connect the MCP Server
Add the DataBlue MCP server to Claude, Cursor, or your own agent runtime with a single config block and your API key.
Agent Calls the Tools
Your agent decides when to search and scrape, calling the tools mid-reasoning just like any other function — no orchestration code from you.
Grounded Responses
Results come back as clean, structured data the model can read directly, so the agent answers from the live web instead of guessing.
AI Agent Questions.
What is MCP and why does it matter for agents?
MCP (Model Context Protocol) is an open standard for connecting tools to AI agents. Because DataBlue ships a native MCP server, any MCP-compatible client — like Claude Desktop or Cursor — can use web search and scraping as built-in tools without you writing a custom integration.
Which agents and clients work with DataBlue?
Anything that speaks MCP, including Claude Desktop, Cursor, and custom agents built on frameworks that support the protocol. If you'd rather not use MCP, the same capabilities are available through the standard REST API.
Why not just let the agent fetch URLs itself?
Raw fetching breaks on JavaScript-rendered pages, returns noisy HTML that wastes tokens, and gets blocked without proxy infrastructure. DataBlue renders the page, strips the noise, and returns clean markdown or JSON — so the agent reads signal, not boilerplate.
How does this handle pages that block bots?
DataBlue manages rendering and anti-bot handling for you behind the API, so your agent can read pages that would otherwise return empty or blocked responses — no proxy pool or browser farm to operate.
Will autonomous runs blow through my quota?
Pricing is credit-based and credits never expire, so unattended runs don't waste a resetting monthly allowance. You can start on the free tier with 1,000 credits a month and scale up with predictable, per-request pricing.
Ship an Agent That Reads the Web.
Start with 1,000 free credits a month — no card, no expiry. Connect the MCP server and give your agent live web tools in minutes.