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 账号 projecttron 发布v0.1.1更新于 Oct 25, 2026
Deterministic signed verification of numeric & financial claims for AI agents & spreadsheets.
发布方自己的服务:Proof Holdings
NumProof 以确定性方式核验数学与财务数字主张,返回 VERIFY、REFUTE 或 ABSTAIN,并附反例与来源信息。
Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/io.github.projecttron%2Fnumproof/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。把它添加到你客户端的 mcpServers 配置中。
{
"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.
来源: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已满足适用检查项的 100%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
holdings.proof官方发布者
Proof Holdings MCP 服务器让助手发起并管理身份与控制权验证(手机、邮箱、域名、钱包),管理证明令牌与委托,并进行校验。

由 GitHub 账号 kivtxs 发布
让助手阅读 Proof of Work 的规则、检查本机是否已有账户,并创建代理账户以发布、投票和支持带证据的主张。

由 GitHub 账号 frankjie3-create 发布
QuietProof 提供免费发现工具,用于浏览一组确定性、只读的审计服务,这些审计按次以 Base 上的 USDC 通过 x402 付费。
com.scriptmasterlabs
远程 MCP 端点,用于在 XRPL 上以 RLUSD 创建、验证和评分发票,并对结算进行自证。

由 GitHub 账号 ZKStamp 发布
远程 MCP 服务器,把 SHA-256 指纹以屏蔽交易写入 BitcoinZ 区块链,生成带日期的存在性证明时间戳。
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