Dokimo MCP

dokimo-mcp

Give an AI agent the ability to verify another agent's revenue claims.

An MCP server exposing Dokimo's evidence checks as tools any MCP client (Claude Desktop, IDE agents, custom agents) can call. It's the "agent that audits agents" — as tools.

Live, clickable version of what these tools do: https://dokimo.augaster.com/agent-audits-agents.html

This is a thin, self-contained client: it calls Dokimo's public endpoints and

implements the public dokimo-merkle-v1 hashing scheme. It contains no proprietary

code. MIT-licensed.

Tools

Verification model: there is no path to verified: true without (1) the caller's (leaf, proof_path) recomputing to the claimed root, and (2) the commitment of (root, rule_version_commitment) — and, for a dokimo-anchor-v2 close, its summary — being anchored on-chain. Tamper one byte → recompute fails. Swap the rule version → the commitment changes → not anchored. A package without summary and binding is checked as legacy v1, which verifies only closes anchored before the v2 cutover.

Honest scope: for one record, checks that its proof reaches the root and that the commitment is anchored on-chain. It does not recompute the close's figures from all its records (that needs the full package, e.g. in /verify.html), and it says nothing about whether a business number is "good." Non-custodial; reads public on-chain state only.

Install & run

pip install dokimo-mcp

dokimo-mcp # runs over stdio

or, from a clone:

pip install . python -m dokimo_mcp

Add to an MCP client

Claude Desktop — add to claude_desktop_config.json:

{

"mcpServers": { "dokimo": { "command": "dokimo-mcp" } } }

If dokimo-mcp isn't on PATH, use the module form:

{

"mcpServers": { "dokimo": { "command": "python", "args": ["-m", "dokimo_mcp"] } } }

Then ask the agent: *"Use Dokimo to verify this evidence package"* (paste one), or *"recompute this Merkle root and tell me if it matches."*

Agent skill

skills/dokimo-verify/SKILL.md tells an agent when and how to use these tools: check the package shape, recompute locally first, ask before sending anything to Dokimo, and report the result for one record without overstating it. Drop the dokimo-verify folder into your agent's skills directory (e.g. ~/.claude/skills/ for Claude Code). It is also listed, free, on Agensi.

Try it

The live demo page embeds a real, anchored evidence package. Fetch it and verify:

import re, json, urllib.request

import dokimo_mcp as d html = urllib.request.urlopen(urllib.request.Request( "https://dokimo.augaster.com/agent-audits-agents.html", headers={"User-Agent": d._UA})).read().decode() pkg = json.loads(re.search(r"const PKG\s*=\s*(\{.*?\})\s*;", html, re.S).group(1)) print(d.verify_evidence_package(pkg)["verified"]) # True

tamper one unit -> False

pkg["leaf"] = pkg["leaf"].replace("1001190933933115", "1001190933933116") print(d.verify_evidence_package(pkg)["verified"]) # False

Hosted / HTTP mode

The default transport is stdio (local use). Set MCP_TRANSPORT=http to serve MCP Streamable HTTP at `/mcp` on $PORT (default 8081) with CORS — the shape hosted platforms like Smithery require. The included Dockerfile + smithery.yaml (runtime: container) are set up for exactly this, so Smithery can build and host it from this repo.

MCP_TRANSPORT=http PORT=8081 dokimo-mcp     # or: docker run -p 8081:8081 <image>

What is Dokimo?

Verifiable revenue infrastructure for autonomous commerce — audit-ready, independently reproducible books for AI-agent machine payments (x402 / AP2 / Stripe), with each figure tamper-evidently committed and anchored on-chain. https://dokimo.augaster.com

License

MIT — see LICENSE.