nidhipati — proof of spend for AI agents MCP Server

by mrpkk Your server? Claim it

answering

nidhipati — proof of spend for AI agents is answering right now. Last checked 6 min ago. It exposes 5 tools. Last commit 25 Oct 2026.

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

Uptime history 26 hours of history · worst hour 75%

26 hours agonow

97.8%

Uptime 24h

89 of 91 checks

Tools

read from the server

951 ms

Response time

average over 24h

Stars

last commit 25 Oct 2026

nidhipati — proof of spend for AI agents does not always answer

Over the last week it answered 97.9% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 6 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

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

Settings → Connectors → Add custom connector, then paste this address

https://rta.lat/nidhipati/mcp

~/.codex/config.toml

[mcp_servers.nidhipati]
url = "https://rta.lat/nidhipati/mcp"

.cursor/mcp.json

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

.vscode/mcp.json

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

Available tools 5

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

audit

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, 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.

reconcile

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 of who the payer was.

reserve

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 treat the result as a statutory audit.

resolve

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.

verify

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 allowed. Do NOT use to move funds or to confirm a transaction on-chain - nothing here reads a chain.

Endpoints

URL	Transport	State	Latency	Checked
https://rta.lat/nidhipati/mcp	streamable-http	answering	810 ms	6 min ago

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nidhipati — proof of spend for AI agents — questions

Answers built from our own checks of this server.

What can nidhipati — proof of spend for AI agents do?

It exposes 5 tools, read directly from the server on our last check. Among them: audit_spend, reconcile_books, reserve_report, resolve_report, verify_receipt. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

Is nidhipati — proof of spend for AI agents working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 89 of 91 checks got a reply (97.8%), average response time 951 ms. The bar chart above shows every period we have measured.

How do I connect nidhipati — proof of spend for AI agents?

Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does nidhipati — proof of spend for AI agents need an API key?

No. nidhipati — proof of spend for AI agents completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 5 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is nidhipati — proof of spend for AI agents?

It answers our handshake in 951 ms on average, which is faster than 7% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.

Is nidhipati — proof of spend for AI agents open source?

The code is open source: it is published under the Apache-2.0 licence, written in Python, 0 stars on GitHub and 1 open issue. The licence covers the code in the repository, not the hosted service at rta.lat, which runs on its operator's own terms.