how it works

How jpcite Evidence Packets work for AI agents

Your AI receives a Japan-regulatory question. It hits the jpcite Evidence Packet bank, retrieves a structured JSON envelope (source URL, fetched-at, known gaps, Ed25519 attestation), then answers using verified evidence instead of long-context retrieval. Two paths: browser AI uses Apple Pay 1-tap, CLI AI uses MCP integration.

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Three-step funnel

  1. Discover — Browse the catalogue at /en/packets/ or call jpcite.list_packets() from your AI agent over MCP.
  2. Verify — Free anonymous evaluation gives 3 requests/day per IP (no signup, resets at JST next-day 00:00). The returned envelope contains source_url, source_fetched_at, known_gaps, exclusion/prerequisite rules, and an Ed25519 attestation.
  3. Integrate and pay — Pay-as-you-go ¥3 per billable unit. Stripe metered billing (qualified Japanese invoice issued automatically) or x402 USDC native payment over HTTP 402 (no API key required, <2 sec settlement).

Two integration paths

Browser AI (Claude.ai / ChatGPT / Perplexity)

Your agent calls the REST endpoint and surfaces an Apple Pay 1-tap purchase link. The Evidence Packet is unlocked within seconds and embedded into the answer.

CLI AI (Cursor / Claude Code / Windsurf)

Install the MCP server: npx @bookyou/jpcite or uvx autonomath-mcp. The agent calls jpcite tools natively over MCP stdio. Stripe metered billing or x402 wallet auto-tops-up.

What's in an Evidence Packet

FieldMeaning
source_urlPrimary public-source URL (METI / MAFF / NTA / Courts / e-Stat / etc.)
source_fetched_atISO-8601 timestamp when jpcite last crawled the source (≤24 h for hot packets)
known_gapsExplicit known limitations (12 small-municipality programs lack a dedicated CMS page)
exclusion_rules181 codified exclusion + prerequisite rules (125 exclude + 17 prerequisite + 15 absolute + 24 other)
citation_candidatesSuggested citation form for the LLM answer step
attestationEd25519 signature over the packet JSON for tamper-evidence

Why agents save tokens with jpcite

Thesis: Sonnet 4.6 / Haiku / GPT-4o-mini / Gemini Flash + jpcite Evidence Packet ≈ Opus 4.7 7-turn over raw Japanese government PDFs, at 1/17 – 1/167 of the LLM token cost. The structured ground truth Opus would re-derive each turn is already in the packet.

Next steps