Krawl

Agent-native deep-research API — recursive tree search, multi-model intelligence, keyless x402 payments, and crypto tools

Krawl is an autonomous deep-research API that performs recursive breadth×depth tree search, synthesizes findings into a cited report with source verification, and streams progress via SSE events. It is built for AI agents: drop in a skill, authenticate with an API key, or let an autonomous agent pay per call with x402 — no account, no signup.

Built with FastAPI and litellm for multi-provider LLM routing. No agent framework — raw tool-calling with a 4-tier model strategy across AWS Bedrock and Anthropic, with cross-provider fallback to survive an outage.

Key Capabilities

  • Recursive research tree — parallel queries at each depth level, learning extraction, gap detection, automatic recursion
  • STORM perspective discovery — multi-perspective research inspired by Stanford's STORM methodology
  • Multi-pass synthesis — gap check → revise cycles with quality scoring (Opus 4.7 for final synthesis)
  • 4-tier model strategy — Haiku for high-volume tasks, Sonnet for research/planning, Opus for synthesis, with cross-provider fallback
  • Cross-session memory — knowledge base that persists learnings across research sessions
  • 9 research modes — deep, quick, crypto, token-analysis, protocol-research, whale-tracking, narrative, risk-assessment, yield-strategy
  • Document upload — PDF, TXT, MD, CSV, JSON — up to 5 files, 10MB each
  • 8 research templates — pre-built query patterns for common research tasks
  • Research steering — inject instructions mid-stream to adjust research direction
  • Async batch tasks — submit a research job and poll for the result, no SSE connection held open
  • Structured output — JSON Schema-driven extraction alongside the markdown report
  • Embedded charts — crypto time-series charts rendered from real data
  • Export — PDF, HTML, Markdown, DOCX, and reveal.js slides
  • Lookouts — scheduled recurring research with change detection and webhooks
  • Audit trail — full log of every search, extraction, and synthesis step
  • 27 SSE event types — real-time streaming of every research phase

Agent-Native by Design

  • API keys with plans — multi-user keys, demo keys, per-request cost ceilings, monthly quotas, and usage metering. See Authentication.
  • Keyless x402 payments — an autonomous agent pays per request in USDC on Base. No account, no key handoff. $1.00 per quick krawl, $5.00 per deep krawl. See Payments & x402.
  • MCP server — connect Krawl as a Model Context Protocol tool, with unauthenticated discovery and gated tool calls.
  • OpenAI-compatible shim — point any OpenAI client at /v1/chat/completions and get a cited research report back.
  • Discovery — agent.json, skill.md, MCP manifest, and /.well-known resources for autonomous agents. See Agents & MCP.

Architecture at a Glance

Client POST /research { query, mode, breadth, depth_levels }
  │
  ├─ Phase 1: Planning (Sonnet 4.6)
  │    └─ Structured research plan with topics and tasks
  │
  ├─ Phase 1.5: STORM Perspective Discovery (Haiku 4.5)
  │    └─ 3-5 research perspectives with key questions
  │
  ├─ Phase 2: Recursive Tree Search
  │    ├─ Generate N queries (Haiku 4.5) × depth levels
  │    ├─ Execute searches in parallel (Exa, X, GitHub, crypto, etc.)
  │    ├─ Extract learnings (Sonnet 4.6)
  │    ├─ Detect knowledge gaps (Sonnet 4.6)
  │    └─ Recurse with depth-1, breadth/2 if gaps remain
  │
  ├─ Phase 3: Verified Synthesis (Opus 4.7, 1 call)
  │    ├─ Gap check → optional re-synthesis
  │    └─ Multi-pass review → revise loop (up to 2 passes)
  │
  └─ SSE stream: plan → perspectives → queries → sources → learnings → report_chunk → result

Quick Start

curl -X POST https://api.krawl.sh/research \
  -H "Content-Type: application/json" \
  -H "X-API-Key: your-key" \
  -d '{"query": "What is the current state of AI agents?", "mode": "deep"}'

The response is an SSE stream. See SSE Events for all event types.

No key? Grab a demo key with no signup:

curl -X POST https://api.krawl.sh/auth/demo-key

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