verify_claim
Exactly verify a math/finance claim (VERIFY/REFUTE/ABSTAIN) with a counterexample when false. Use before trusting any AI-produced number, sum, percentage, or formula.
claim必填
io.github.projecttron由 GitHub 帳號 projecttron 發布v0.1.1更新於 Oct 25, 2026
Deterministic signed verification of numeric & financial claims for AI agents & spreadsheets.
發布方自己的服務:Proof Holdings
NumProof 以確定性方式核驗數學與財務數字主張,回傳 VERIFY、REFUTE 或 ABSTAIN,並附上反例與來源資訊。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.projecttron%2Fnumproof/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"numproof": {
"type": "http",
"url": "https://numproof.com/mcp"
}
}
}The deterministic numeric truth layer for AI agents and spreadsheets.
Your agent writes "gross margin improved from 42.1% to 44.8%" or "the workbook is internally consistent" — NumProof tells you, deterministically, whether that number is VERIFY, REFUTE, or ABSTAIN, with a counterexample, cell/formula provenance, and a signed, machine-checkable audit bundle. It's exact arithmetic and symbolic math — not an LLM judging another LLM.
xlsx/csv rows: footing, cross-footing, balance-sheet ties, margins, formula cells — with provenanceThis repo is the open-source client (SDK + MCP). The verification engine runs as a hosted service —
pip install numproof, point it at the API, done. (Same shape asstripe-python: the SDK is open, the engine is the service.)
Live demo (no key): https://numproof.com · Docs: https://numproof.com/docs
No install? It's just HTTP:
Free API key:
Every audit/diff/covenant result can be returned as a signed bundle + human-readable HTML/PDF
report (format="zip"). Recipients verify it without trusting you or NumProof:
NumProof ships an MCP server so Claude / OpenAI-style agents can call it as a tool — gate every numeric claim before it reaches a user, report, or auditor.
Or point any MCP client at the hosted descriptor: https://numproof.com/mcp.json.
See examples/ for runnable scripts (verify, audit, covenants, agent-gate, MCP).
Verify the numbers your agent emits before it acts, in the framework you already use
(numproof/integrations/ — each lazily imports its framework, so the numproof client stays stdlib-only):
numproof.integrations.openai_agents (output guardrail / tripwire)numproof.integrations.pydantic_ai (output validator; raises ModelRetry with the counterexample so the model self-corrects)numproof.integrations.langchain (a NumProof Tool + an output checker)numproof.integrations.deepeval (a deterministic NumProofMetric: VERIFY → score 1.0, REFUTE → score 0.0 with the counterexample on .reason)numproof.integrations.guardrails (a Hub Validator: REFUTE → FailResult with the counterexample, so your on_fail action — reask/fix/exception — fires)VERIFY → pass · REFUTE → block/retry with the counterexample · ABSTAIN → pass-through (configurable). Runnable examples in examples/; install only the framework you use.
Any verdict can be returned as a signed Verification Receipt — and you re-check it offline, trusting neither the transport nor NumProof:
It recovers the EIP-191 signer (tamper-evident) and, for value/agg/identity/sequence
claims, independently re-derives the verdict with stdlib Fraction + sympy. A tampered
field, a wrong signer, or a verdict that doesn't actually hold all fail loudly — even a receipt
NumProof itself mis-signed is caught by the re-derivation. An agent can recompute a number for
itself; it cannot issue an independent, signed attestation a second party will accept. That
independence — not the arithmetic — is the product. Format + spec: RECEIPT_FORMAT.md.
Generic "AI guardrails" use a model to grade a model — probabilistic, and itself can hallucinate.
NumProof recomputes the math exactly (rational arithmetic + symbolic identity checking) and
returns a reproducible verdict with a trace. When it can't prove something it says ABSTAIN
rather than guess. For finance, regulated, and agent workflows, "the number is provably right"
beats "another model thinks it looks right." Full table: comparison.md.
The numproof Python SDK (NumProof client), the MCP server, and runnable examples — all thin
HTTP clients to the hosted API. MIT licensed. The verification engine, finance audit logic,
formal (Lean) proof tier, and signing are the hosted service and are not in this repo.
Found a wrong verdict? Open an issue with the exact claim — correctness is the whole product.
來源:README.md,提交 63b28f4
Exactly verify a math/finance claim (VERIFY/REFUTE/ABSTAIN) with a counterexample when false. Use before trusting any AI-produced number, sum, percentage, or formula.
claim必填Audit spreadsheet-like rows for footing, balance-sheet ties, common margins, and cell provenance.
rows必填Compare two report versions by numeric row labels with provenance.
rows_after必填rows_before必填Evaluate threshold/covenant rules over spreadsheet-like rows with provenance. Use either rules or rule_pack.
rows必填rulesrule_pack已滿足適用檢查項的 100%
該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。
holdings.proof官方發布者
Proof Holdings MCP 伺服器讓助理發起並管理身分與控制權驗證(手機、電子郵件、網域、錢包),管理證明權杖與委派,並進行驗證。

由 GitHub 帳號 kivtxs 發布
讓助理閱讀 Proof of Work 的規則、檢查本機是否已有帳號,並建立代理帳號以發佈、投票與支持附證據的主張。

由 GitHub 帳號 frankjie3-create 發布
QuietProof 提供免費探索工具,用來瀏覽一組確定性、唯讀的稽核服務,這些稽核按次以 Base 上的 USDC 透過 x402 付費。
com.scriptmasterlabs
遠端 MCP 端點,用於在 XRPL 上以 RLUSD 建立、驗證與評分發票,並對結算進行自證。

由 GitHub 帳號 ZKStamp 發布
遠端 MCP 伺服器,把 SHA-256 指紋以遮蔽交易寫入 BitcoinZ 區塊鏈,產生附日期的存在性證明時間戳。
pip install numprooffrom numproof import NumProof
np = NumProof.from_env() # NUMPROOF_API_KEY (get a free key: see below)
print(np.verify("120 + 90 + 340 + 15 == 565"))# {'verdict': 'VERIFY', 'certificate': 'EXACT_ARITHMETIC', ...}
print(np.verify("a 50% loss needs a 100% gain to break even")) # VERIFY: (1-0.5)*(1+1.0)==1print(np.verify("two 10% raises equal a 21% total increase")) # VERIFYprint(np.verify("operating margin is 18% when EBIT is 180 and revenue is 1000")) # VERIFYcurl -s https://numproof.com/demo -H 'Content-Type: application/json' \ -d '{"claim":"gross margin is 60% when gross profit is 600 and revenue is 1000"}'curl -s https://numproof.com/signup -X POST -H 'Content-Type: application/json' -d '{}'rows = [["Revenue", 1000], ["COGS", 400], ["Gross Profit", 600], ["Gross Margin", "60%"]]print(np.audit_rows(rows)["verdict"]) # PASS (600/1000 == 60%, footing, ties, ...)
# covenant rule packs: DSCR, Debt/EBITDA, current ratio, custom thresholdsprint(np.covenant_rows( [["EBITDA", 500], ["Debt Service", 300], ["Debt", 1200]], rule_pack="credit_covenants_basic",)["verdict"])curl -s https://numproof.com/audit/verify -H 'Content-Type: application/json' -d @bundle.json# {"valid": true, "verdict": "PASS", "signer": "0x...", ...}python -m numproof.mcp{ "mcpServers": { "numproof": { "command": "python", "args": ["-m", "numproof.mcp"] } } }# OpenAI Agents SDK — output guardrail that trips on REFUTEfrom agents import Agentfrom numproof.integrations.openai_agents import numproof_output_guardrailagent = Agent(name="...", instructions="...", output_guardrails=[numproof_output_guardrail()])pip install "numproof[verify]"numproof-verify receipt.json --signer 0x<published-NumProof-signer># OK independently re-derived + signature valid