nidhipati — proof of spend for AI agents

Name: nidhipati — proof of spend for AI agents
Author: mrpkk

by mrpkkversion 0.7.1i★ –iComputer or cloud

Registry nameio.github.mrpkk/nidhipati

Install

Overview

Description from the maker (original English)

Proof-of-spend and reserve checks for AI agents: receipts, spend audit, NAV, reconciliation.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi3 of 3 passedChecked from public information; code not scanned yet
UsageiVery new★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Computer or cloud
Transport: stdio, Streamable HTTP
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 3 of 3 passed
Runs on the maker’s server: what you ask it goes through their server.
Can do 5 things (tools) verify_receipt, audit_spend, reserve_report, resolve_report …
The registry lists no key to fill in.

You need

Runs in the cloudNothing to install; it connects over the internet
DockerDocker installed

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

Open Settings → Connectors
Press Add custom connector
Paste the address below and press Add
If it asks you to sign in, sign in with the maker

https://rta.lat/nidhipati/mcp

Or run it on your computer

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "nidhipati": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/mrpkk/nidhipati:0.6.0"
      ]
    }
  }
}

Run this in your terminal

claude mcp add --transport http nidhipati https://rta.lat/nidhipati/mcp

Or run it on your computer

claude mcp add nidhipati -- docker run -i --rm ghcr.io/mrpkk/nidhipati:0.6.0

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "nidhipati": {
      "url": "https://rta.lat/nidhipati/mcp"
    }
  }
}

Or run it on your computer

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "nidhipati": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/mrpkk/nidhipati:0.6.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "nidhipati": {
      "type": "http",
      "url": "https://rta.lat/nidhipati/mcp"
    }
  }
}

Or run it on your computer

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "nidhipati": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/mrpkk/nidhipati:0.6.0"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

Open ChatGPT on the web → Settings → Connectors (Apps)
Press Create or Add (some plans need Developer mode under Advanced first)
Paste the address below, give it a name and save
If it asks you to sign in, sign in with the maker

https://rta.lat/nidhipati/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Tool names and descriptions exactly as the server reported them on Nov 6, 2026. The maker wrote them, not us; we show them as plain text.

verify_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 allow
audit_spend
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, bud
reserve_report
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 tr
resolve_report
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.
reconcile_books
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

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account mrpkk, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
✓ Pass
Endpoint responds
Responded in 623 ms (HTTP 200)
– Not applicable
Sign-in with OAuth
No sign-in needed
✓ Pass
No hidden instructions in tool descriptions
Read 5 tool descriptions and found no hidden instructions to the AI

Compared with others in Otheri

More stars than 0% of the other 18669 servers in this category
Published to the registry more recently than 89% of the other 18669 servers in this category
Basic checks equal to or better than 100% of the other 18669 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is nidhipati — proof of spend for AI agents safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.7.1) reached the registry 5 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, CLIO Paraview

Alternatives

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Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Nidhipati

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.

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

Reserve and NAV report

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.

nidhipati-reserve report examples/reserve.example.json --key keys/private.pem --markdown report.md

NAV = Σ quantity × price × (1 − haircut) − liabilities

ratio = NAV / supply

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.

Resolution evidence

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.

nidhipati-resolve report examples/resolve.example.json --key keys/private.pem --markdown report.md

Details: docs/RESOLUTION-EVIDENCE.md.

Reconciliation

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.

nidhipati-reconcile run examples/invoices.example.csv examples/transactions.example.csv --csv matches.csv

Details: docs/RECONCILIATION.md.

MCP server (for agents, not shells)

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.

{"jsonrpc":"2.0","id":1,"method":"tools/call",

"params":{"name":"reserve_report","arguments":{"reserve":{...}}}}

python3 -m nidhipati_proof.mcp_stdio      # stdio transport

docker build -t nidhipati-mcp . && docker run -i --rm nidhipati-mcp

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.

Free scan, and what it costs after

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 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:

- uses: mrpkk/nidhipati@v0.2.0

with: records: billing/agent-spend.csv policy: billing/policy.json

Quick start

python3 -m pip install -e .[dev]

python3 -m pytest -q python3 -m nidhipati_proof.cli verify examples/proof-of-spend.example.json --pubkey

What it checks

schema and canonical JSON;
Ed25519 signature;
mandate expiry vs settlement time;
amount, asset, network, payee;
usage.quantity × usage.unit_price vs payment;
refund ≤ payment;
verdict allow for a settled payment;
receipt ID/replay (v0.2 store).

Agent spend audit

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:

Finding	What it means
`duplicate_charge`	the same receipt twice, or an equal charge within 120s with no receipt at all
`price_escalation`	settled above the authorised quote by more than 1%
`failed_but_billed`	status failed/error and still charged
`missing_refund`	authorised 10, used 4, nothing returned
`runaway_loop`	more than 30 calls a minute from one agent
`model_overpay`	far above this agent's own median for the same tool and model (an estimate)
`unknown_asset` / `unknown_network` / `missing_payee`	the record does not say where the money went
`budget_bypass` / `budget_exceeded`	no policy file: the limit lives in a prompt; with a policy, the agent is over it

python3 -m pip install -e .

nidhipati-spend audit examples/spend-sample.csv --policy examples/spend-policy.example.json nidhipati-spend audit records.csv --json > report.json

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.

Honest limits

v0.1 does not verify the on-chain transaction; onchain_verified=false is explicit.
It is not a statutory audit, legal, tax, or investment advice.
It does not guarantee the service was good; it proves the payment was within mandate.
No custody, no money transmission, no token.

Docs

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.

License

Apache-2.0.

nidhipati — proof of spend for AI agents

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Or run it on your computer

Or run it on your computer

Or run it on your computer

Or run it on your computer

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

CLIO Paraview

README from the maker

Nidhipati

Reserve and NAV report

Resolution evidence

Reconciliation

MCP server (for agents, not shells)

Free scan, and what it costs after

Quick start

What it checks

Agent spend audit

Honest limits

Docs

License