io.github.mrpkk由 GitHub 账号 mrpkk 发布v0.7.1更新于 Nov 4, 2026
Proof-of-spend and reserve checks for AI agents: receipts, spend audit, NAV, reconciliation.
发布方自己的服务：Proof Holdings
校验 AI 代理的签名支出凭证，并审计代理花费、储备净值、结算证据与发票对账。
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.mrpkk%2Fnidhipati/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": {
"nidhipati-proof-of-spend-for-ai-agents": {
"type": "http",
"url": "https://rta.lat/nidhipati/mcp"
}
}
}Proof of Spend for AI agents. A signed receipt that proves what an agent was authorized to pay, what it actually paid, what it used and what was refunded. Not a token, not custody, not another payment rail.
Рельсы двигают деньги. Nidhipati доказывает, что движение было правильным.
[tests] [MCP Registry] [Glama] [license]
Status: v0.6 — five CLIs, an MCP server, 94 tests, official MCP Registry and Glama listing.
Site: https://mrpkk.github.io/nidhipati/
Free browser audit (no signup): https://mrpkk.github.io/nidhipati/free-spend-audit.html
BusinessMCP directory: https://businessmcp.com/mcp-servers/nidhipati
Private scan request: https://github.com/mrpkk/nidhipati/issues/new?template=free-spend-audit.yml
For tokenised assets: the issuer's own numbers turned into a NAV with explicit formulas and an
evidence hash per line. The verdict is backed, underbacked, or incomplete — and the ratio
is refused when any line has no price, because a number computed over half a reserve is not
a number.
The statement hash is compared with the file if you provide it. The disclaimer travels inside the signed document. Details and the partner/legal checklist: docs/RESERVE-REPORT.md.
When a market resolves and someone disagrees, the question is whether the resolver's sources
say what the resolver claims and whether they agree with each other. The report answers with
four verdicts — supported, disputed, single_source, insufficient — and never picks a
winner.
Details: docs/RESOLUTION-EVIDENCE.md.
Invoices on one side, transfers on the other. The report names what is closed, what nobody paid, and what arrived without an invoice — a transfer that duplicates a payment is counted once, never twice.
Details: docs/RECONCILIATION.md.
The same five checks over the Model Context Protocol: verify_receipt, audit_spend,
reserve_report, resolve_report, reconcile_books. Input is data, never a file path and never
a network call; the answers are the same reports the CLIs produce, including the refusal to print
a backing ratio when a line has no price.
Five tools, all read-only: no custody, no keys, no chain read.
Official MCP Registry: https://registry.modelcontextprotocol.io/v0/servers?search=nidhipati (io.github.mrpkk/nidhipati, OCI ghcr.io/mrpkk/nidhipati:0.6.0).
Glama listing: https://glama.ai/mcp/servers/mrpkk/nidhipati.
Send records of what your agents spent and get the audit back — no card. The browser audit needs no account; a human review can go by email or Telegram, no GitHub needed: email [email protected] or Telegram with the downloaded report (not raw rows). GitHub is optional: open a private scan request; the issue is public, so ask the question only and never paste records or keys. Paid: first 3 audits $1,250; then $2,500 fixed, $1,500/mo retainer, or 20% of verified savings. $5,000 finding guarantee (identified overcharges, not recovery). Full terms, including what is not included: docs/OFFER.md.
In CI, on every run:
usage.quantity × usage.unit_price vs payment;allow for a settled payment;A signed receipt proves one charge. A bill proves a month. The audit reads the records you already have (CSV or JSON) and names the rows where money left without a reason:
Exit code 1 when there is an error — a pipeline can fail on it. The report keeps three
amounts apart on purpose: spent without a reason (duplicates, escalation, failed calls,
refunds not returned), above the usual price (an estimate, not proof), and over the
limit (the money may have been spent on real work).
The sample is synthetic and labelled: it contains every finding once, so you can see what a report looks like before trusting it with real invoices.
onchain_verified=false is explicit.SPEC.md — product, architecture, modules, SEO, monetization, 30/60/90.PROGRESS.md — slices, acceptance, metrics.docs/PROMPT-AND-IDEAS.md — prompt and decisions for RAG.docs/SEO-MONETIZATION.md — keywords, pages, funnel, pricing.docs/LAUNCH-KIT.md — Show HN, Reddit, Product Hunt, X/LinkedIn copy.docs/DEMO.md — real commands and sample output.docs/AGENT-SPEND-AUDIT.md, docs/RESERVE-REPORT.md, docs/RESOLUTION-EVIDENCE.md, docs/RECONCILIATION.md — module rules.schemas/proof-of-spend.schema.json — v0.1 schema.examples/proof-of-spend.example.json — example.Apache-2.0.
来源：README.md，提交 2c3d835
Verify an agent payment receipt
Check a signed proof-of-spend receipt offline: schema, Ed25519 signature, mandate expiry, positive amount, quantity*unit_price == amount, refund not above payment. Use when an agent or provider returns a receipt and you need to know whether it actually proves the charge was allowed. Do NOT use to move funds or to confirm a transaction on-chain - nothing here reads a chain.
receipt必填public_key必填Audit an agent's spending records
Find duplicates, price escalation, failed-but-billed calls, runaway loops, missing refunds, model overpay, unknown asset/network and budget breaches in a list of settled agent calls. Returns three separate amounts (money without a basis, estimate above the agent's own median, budget overrun) instead of one sum, because adding them together would overstate what can be recovered. Do NOT use as a statement of money actually returned.
policyrecords必填Reserve and NAV report for a tokenised asset
Turn an issuer's reserve lines into a NAV with explicit formulas and a sha256 evidence hash per line. Verdict is backed, underbacked, or incomplete - and the backing ratio is refused (null) when any line has no price, because a ratio over half a reserve is not a number. Do NOT treat the result as a statutory audit.
reserve必填Resolution evidence for a prediction market
Weigh the sources a resolver says it read against the declared outcome. Verdicts: supported, disputed, single_source, insufficient. A conflict is reported as a conflict, never averaged. Do NOT use to trade or to place a position.
market必填Reconcile invoices against transfers
Match invoices to stablecoin transfers by memo first, then exact amount and asset inside the invoice window. Names what is left over in both directions: invoices nobody paid, money nobody invoiced, invoices paid twice. A duplicate is counted once, never twice. Do NOT use as proof of who the payer was.
invoices必填transactions必填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。
nidhipati-reserve report examples/reserve.example.json --key keys/private.pem --markdown report.mdNAV = Σ quantity × price × (1 − haircut) − liabilitiesratio = NAV / supplynidhipati-resolve report examples/resolve.example.json --key keys/private.pem --markdown report.mdnidhipati-reconcile run examples/invoices.example.csv examples/transactions.example.csv --csv matches.csv{"jsonrpc":"2.0","id":1,"method":"tools/call", "params":{"name":"reserve_report","arguments":{"reserve":{...}}}}python3 -m nidhipati_proof.mcp_stdio # stdio transportdocker build -t nidhipati-mcp . && docker run -i --rm nidhipati-mcp- uses: mrpkk/[email protected] with: records: billing/agent-spend.csv policy: billing/policy.jsonpython3 -m pip install -e .[dev]python3 -m pytest -qpython3 -m nidhipati_proof.cli verify examples/proof-of-spend.example.json --pubkey <base64url>python3 -m pip install -e .nidhipati-spend audit examples/spend-sample.csv --policy examples/spend-policy.example.jsonnidhipati-spend audit records.csv --json > report.json