Bluefield
Choosing a web scraping API for AI agents
The best web scraping API for AI agents depends on your workload, but for agents that act unattended two things matter most: provenance (can the agent prove what it fetched?) and agent-native access (can it discover and call the tool with no glue code?). Bluefield signs every live result and ships an MCP server, an OpenAPI spec, and llms.txt, with a fast median response.
What makes a web data API good for agents?
Agent-friendly web data APIs return LLM-ready Markdown or structured JSON, are callable as tools (MCP / OpenAPI), respond quickly at the median, and — for unattended use — provide a verifiable record so the agent’s output can be trusted and audited.
- MCP
- Model Context Protocol — registers Bluefield’s tools directly in an agent runtime.
- Provenance
- A signed, verifiable record an agent can store with each result.
- LLM-ready output
- Clean Markdown / structured JSON, ready for retrieval without HTML parsing.
Bluefield capabilities
| Capability | Detail |
|---|---|
| MCP server | npx @bluefields/mcp-server — scrape, map, crawl, search, extract |
| OpenAPI + llms.txt | Discoverable + callable by coding agents and tool-use |
| Signed results | Every live fetch is signed + verifiable — trust for unattended agents |
| Fast median | 783 ms p50 in our latest benchmark (see /benchmarks for p95) |
| Watch mode | Signed webhook when a monitored page changes |
Frequently asked questions
- How does an agent call Bluefield?
- Via the MCP server (registered in the agent config) or the REST API with any HTTP client. The OpenAPI spec and llms.txt make both discoverable.
- Why does provenance matter for agents?
- An autonomous agent acts on data without a human checking it. A signed result lets the agent — or its owner, or an auditor — prove what was fetched and that it has not changed.
- What output format is best for RAG?
- Markdown from /scrape for single pages; /extract for schema-constrained JSON; /batch/scrape for bulk ingestion.