中小経営者 補助金 companion (A5)

業種 × 地域 × 規模 × ライフサイクル 段階で利用可能な補助金 / 融資 / 税制 / 認定 を 1 packet。同業同地域の採択事例 + 排他ルール + 申請 期限カレンダーを併載。最終判断は税理士 / 行政書士 confirm 経路。

誰のためか

中小経営者 (SME-Owner) コホート. 月次 100 req 想定 (¥3/req)。

1 query で返るもの (package_kind)

evidence_packet, artifact_pack, watch_digest

呼び出される heavy / composed endpoint

• POST /v1/jpcite/route
• POST /v1/jpcite/preview_cost
• POST /v1/cases/cohort_match
• POST /v1/programs/full_context
• POST /v1/evidence/packets/query

SDK example — Python (jpcite-mcp / autonomath-mcp PyPI)

# A5 SME Subsidy Companion — Python (jpcite-mcp)
import os
import httpx

JPCITE_API = "https://api.jpcite.com"
API_KEY = os.environ["JPCITE_API_KEY"]  # see https://jpcite.com/dashboard

def fetch_sme_packet(houjin_bangou: str) -> dict:
    # 1. Free preflight — no charge until accepted_artifact delivery.
    preview = httpx.post(
        f"{JPCITE_API}/v1/jpcite/preview_cost",
        headers={"X-API-Key": API_KEY, "X-Client-Tag": "sme-001"},
        json={"outcome_contract_id": "A5_sme_subsidy_companion",
               "input": {"houjin_bangou": houjin_bangou}}
    ).raise_for_status().json()
    assert preview["cap_passed"], "outcome exceeds cap — adjust max_price_jpy"

    # 2. Execute packet — charges 27 billable units (=¥27).
    packet = httpx.post(
        f"{JPCITE_API}/v1/jpcite/execute_packet",
        headers={"X-API-Key": API_KEY,
                  "X-Client-Tag": "sme-001",
                  "X-Jpcite-Scoped-Cap-Token": preview["scoped_cap_token"],
                  "Idempotency-Key": f"sme-{houjin_bangou}-2026-05"},
        json={"outcome_contract_id": "A5_sme_subsidy_companion",
               "input": {"houjin_bangou": houjin_bangou},
               "max_price_jpy": 900}
    ).raise_for_status().json()
    return packet  # contains source_url[], fetched_at, known_gaps[], evidence[]

SDK example — TypeScript (Bedrock MCP / OpenAI tool-use)

// A5 SME Subsidy Companion — TypeScript (Bedrock / OpenAI tool-use)
import { JpciteClient } from "@jpcite/sdk";  // wraps OpenAPI 219 paths

const client = new JpciteClient({
  baseUrl: "https://api.jpcite.com",
  apiKey: process.env.JPCITE_API_KEY!,
  clientTag: "sme-001",  // 顧問先 fan-out attribution
});

export async function fetchSMEOwnerPacket(houjinBangou: string) {
  const preview = await client.previewCost({
    outcome_contract_id: "A5_sme_subsidy_companion",
    input: { houjin_bangou: houjinBangou },
  });
  if (!preview.cap_passed) throw new Error("over cap");

  const packet = await client.executePacket({
    outcome_contract_id: "A5_sme_subsidy_companion",
    input: { houjin_bangou: houjinBangou },
    max_price_jpy: 900,
    scopedCapToken: preview.scoped_cap_token,
    idempotencyKey: `sme-${houjinBangou}-2026-05`,
  });
  return packet;  // { source_url[], fetched_at, known_gaps[], evidence[] }
}

Claude Code .mcp.json snippet

{
  "mcpServers": {
    "jpcite": {
      "command": "npx",
      "args": [
        "-y",
        "autonomath-mcp"
      ],
      "env": {
        "JPCITE_API_KEY": "${env:JPCITE_API_KEY}",
        "JPCITE_DEFAULT_OUTCOME": "A5_sme_subsidy_companion",
        "JPCITE_CLIENT_TAG": "sme-001"
      }
    }
  }
}

jpcite ¥300 / 月 vs LLM API replacement

cheapest LLM tier (Haiku 4.5) でも jpcite の 0.5x コスト。 さらに LLM 単独は出典 URL を hallucinate するため、 一次資料 URL + fetched_at + known_gaps は jpcite でしか得られない。

コホート 別コスト比較表を見る →

1 call ≈ 人手 ¥900 相当

30-90 分の一次資料調査 + 名寄せ + 出典確認を 1 query で代替。 代替時給 ¥3,000 換算で 1 packet ≒ ¥900。 jpcite ¥3 / packet との差分が ROI。

使い始める

1. /dashboard で API キー発行 (匿名 3 req/日無料)
2. Python: pip install autonomath-mcp
3. Claude Code: .mcp.json 上記 snippet を貼り付け
4. getting-started 経由で 1 packet を取得

関連リソース

• API reference (219 path)
• MCP tools (146 default-gate)
• cookbook (15 recipes)
• 中小経営者 向け コホート landing
• outcome catalog (450 outcome)