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PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

Agent Receipts

作者:webaesbyaminバージョン 0.6.0i★ –iパソコンで動く
レジストリ名io.github.webaesbyamin/agent-receipts

インストール

概要

作者による説明(英語の原文)

Ed25519-signed receipts for every AI agent action. Local-first, verifiable, no server required.

PopNx MCPの3つの柱

この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: パソコンで動く
  • トランスポート: stdio
  • カテゴリ: その他

インストール

使っているAIアプリを選んで、設定をコピーしてください。

インストールの前に

  • 基本チェック:1項目中1項目に合格
  • あなたのパソコンで、あなたのユーザーと同じ権限(ファイル、ネットワーク、アプリ)で動きます。
  • レジストリには、入力が必要なキーは載っていません。

必要なもの

  • npmNode.jsのインストール(npxコマンドに必要)

どのアプリを使っていますか?

上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。

Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます

{
  "mcpServers": {
    "agent-receipts": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-receipts/mcp-server"
      ]
    }
  }
}

ターミナルでこれを実行します

claude mcp add agent-receipts -- npx -y @agent-receipts/mcp-server

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

{
  "mcpServers": {
    "agent-receipts": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-receipts/mcp-server"
      ]
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

{
  "servers": {
    "agent-receipts": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@agent-receipts/mcp-server"
      ]
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。

選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

できること

パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名は、リポジトリを所有するGitHubアカウント webaesbyamin で確認済みです

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • – 対象外

    エンドポイントが応答する

    これはパソコンで動くため、インターネット上のエンドポイントはありません

  • – 対象外

    OAuthでサインイン

    パソコンで動き、代わりにローカルの設定を使います

  • … 未チェック

    ツールの説明に隠れた指示がない

    パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです

その他のほかのサーバーとの比較i

  • このカテゴリのほかの18348件のうち0%よりスターが多い
  • このカテゴリのほかの18348件のうち87%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの18348件のうち100%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

Agent Receiptsは安全ですか?

当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。

パソコンで動きますか、それともクラウドですか?

あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(0.6.0)がレジストリに届いたのは6 日前です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。

代わりに使えるものは?

同じカテゴリには:Spec Driven Development, Remote Desktop Commander, 好縮 Short

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

クラウドで動く★ 211一昨日更新
インストール

好縮 Short

作者:gooonamee

Smart URL shortener: create, tag and track short links on s.gooo.name.

クラウドで動く今日更新
インストール

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

Agent Receipts

Your agent says it's done. Prove it.

Agent Receipts gives the work your AI agent does a signed receipt: what went in, what came out, which model ran, how long it took and what it cost. Each receipt is signed with Ed25519 and linked to the one before it, so anyone can check it offline with your public key, without trusting you, your server or the agent. Change one byte and it no longer verifies.

claude mcp add agent-receipts -- npx @agent-receipts/mcp-server

receipts.webaes.com (what it is, install, and a page that signs itself) · demo.receipts.webaes.com (the dashboard with sample data) · verify.webaes.com (a real issuer's verify page) · by Webaes

Automatic receipts · Get started · Magic Folder · Memory · How it's different


Automatic receipts

Get a signed receipt for everything your agent does, without changing how you work.

Claude Code: one command. Every file edit, file write, notebook edit and shell command gets its own signed receipt, chained per session, and the session ends with a summary (actions, files touched, duration):

npx @agent-receipts/cli hooks install            # or --scope project / --scope local

It shows the change to Claude Code's settings.json and asks first; hooks uninstall takes it out again. Or install it as a Claude Code plugin:

claude plugin marketplace add webaesbyamin/agent-receipts

claude plugin install agent-receipts@agent-receipts

Any MCP server: the proxy. Put it in front of a stdio MCP server and every tool call through it is signed (mcp. . ), while every message passes through unchanged:

claude mcp add fs-receipted -- npx -y @agent-receipts/cli proxy --name fs -- npx -y @modelcontextprotocol/server-filesystem ~/Documents

Receipts hold hashes only (inputs, outputs, and each changed file), never commands, file contents or results. See them in the dashboard's Sessions view (npx @agent-receipts/dashboard) or check one with agent-receipts verify-chain . Setup for Claude Desktop and Cursor: CLI README.

What these receipts do and don't prove:

  • They prove what Claude Code (or the MCP client) reported, signed outside the agent. The hook and the proxy run as separate processes, and each receipt is signed the moment the tool finishes, so the agent can't edit a receipt afterwards without breaking it. They don't prove the work was right, only what was done and that the record hasn't changed.
  • `claude -p` can stop the last one. In a scripted run, Claude Code stops background hooks still running when the run ends, so a tool call in the last moment of a run can go unrecorded.
  • The computer's owner controls the keys. Receipts are signed with keys in ~/.agent-receipts on your machine. They show the record wasn't changed after signing; someone who controls that machine could sign a false one. To show others, publish your public key so they know which key to trust.
  • stdio MCP servers only for now. Remote (HTTP) MCP servers aren't covered yet.

Proof

Every memory observation and every action your agent tracks produces a receipt — a signed JSON document with:

  • Ed25519 signature over every field (receipt format v2) — tamper-proof, independently verifiable
  • Input/output hashes — proves exactly what went in and came out (raw data never stored)
  • Timestamps — when it happened, when it completed
  • Agent ID — which agent did it
  • Link to the previous receipt — the hash of the one before it, so a missing receipt shows
  • Provenance chain — trace any memory back to the conversation that created it

This isn't logging. Logs are mutable text files the agent writes about itself. Receipts are cryptographic proof that a third party can verify without trusting you, your server, or the agent.

Everything runs locally
npx @agent-receipts/mcp-server

That's it. No API key. No account. No cloud. No monthly fee. No data leaving your machine. SQLite database in ~/.agent-receipts/. Works offline. Needs Node.js 22.16 or later.

Get Started

Needs Node.js 22.16 or later.

1. Add the MCP Server

Claude Code:

claude mcp add agent-receipts -- npx @agent-receipts/mcp-server

Claude Desktop (claude_desktop_config.json) / Cursor (.cursor/mcp.json):

{

"mcpServers": { "agent-receipts": { "command": "npx", "args": ["@agent-receipts/mcp-server"] } } }

2. Add the System Prompt

This tells your agent when to observe memories, recall context, and track actions — so it works automatically:

npx @agent-receipts/cli prompts claude-code

Copy the output into your project instructions or system prompt.

3. Start Using It

Your agent will now:

  • Call memory_context at the start of sessions to load what it knows about you
  • Call memory_observe when it learns something worth remembering
  • Call track_action when it performs significant actions
  • Sign everything with Ed25519
4. See What's Happening
npx @agent-receipts/dashboard    # Web UI at localhost:3274

npx @agent-receipts/cli stats # Terminal overview npx @agent-receipts/cli memory entities # See what your agent remembers

5. Try Before Installing

Run the interactive demo → — experience memory, verification, and bundle export in 60 seconds. No install required.

Magic Folder: receipts for people who don't code

Drop a file into a folder named after a job ("Write product descriptions", "Fix typos"). An agent does the work, and the result comes back in Done/ with your untouched original and a one-page receipt.html that anyone can check, plus an approval step for anything client-facing.

npm install -g @agent-receipts/magic-folder

magic-folder init ~/"Magic Folder" magic-folder run ~/"Magic Folder" --engine ollama --issuer "Your Studio"

Needs Node 22.16 or later and, for free local jobs, Ollama. Step-by-step for Mac, Windows and Linux: receipts.webaes.com/install.

The runner writes the receipt, not the agent: it hashes the real files and records the model, time and cost itself (on Claude, the cost is the Agent SDK's own estimate and is marked as one; on Ollama it's $0). See packages/magic-folder and the static verify page.

Memory

Your agent gets structured, persistent memory across sessions — people, projects, tools, preferences, facts. Not a flat key-value store. An entity-observation graph where every fact links to the conversation that created it.

# Your agent learns something

memory_observe → "User prefers TypeScript, uses Neovim, building a SaaS called ModQuote"

Next session, it already knows

memory_context → loads everything: entities, observations, relationships, preferences

You can search it

memory_recall → "what tech stack does the user prefer?" → structured results

You can forget (and the forget itself is tracked)

memory_forget → soft delete with audit trail

The agent handles this automatically when you add the system prompt. You don't manage memory manually.

Portable memory bundles

Export your agent's entire memory as a single verifiable file:

npx @agent-receipts/cli memory export > my-project.bundle.json

The bundle includes every entity, observation, relationship, the receipts that created them, and the public key needed to verify everything. Hand it to another agent, another team, or another Agent Receipts instance — they can verify every fact without trusting you.

The Problem

You're building with AI agents. Claude Code refactors your auth module and says "done, all tests pass." Your agent generates a customer quote and says it applied the right pricing. Your assistant remembers your preferences from last week — but you can't see why it thinks that, or whether it's right.

Three things are broken:

  1. Agents forget everything between sessions. Every conversation starts from zero. Context is lost. You re-explain the same things.
  1. When agents do remember, you can't see inside. Platform memory is a black box. You can't see what it stored, when, or why. You can't correct it, export it, or verify it.
  1. There's no proof of what agents actually did. Logs are mutable. Agents write their own logs. "I updated 3 files and all tests pass" — did it? You're trusting the agent's word about its own work.

Why This Exists

The idea came from building ModQuote, a multi-tenant SaaS for automotive protection and detailing shops: PPF, ceramic coatings, window tint.

AI-drafted quotes are on ModQuote's roadmap, and designing that feature raised a question I couldn't answer with the tools I had. If an agent drafts a $2,400 PPF quote and the customer disputes the price, how do I show what vehicle data it received and which pricing rules it applied? Not with a log entry the agent wrote about itself, but with proof that someone outside my system can check.

Memory tools could tell me what an agent remembered, and observability tools could tell me what happened inside my own pipeline. Neither gave me a record that a customer, a client or an auditor could verify without trusting me.

So I built Agent Receipts first, as its own open-source project. When AI quoting ships in ModQuote, every quote will come with a signed receipt. Until then, Agent Receipts stands on its own: any agent, any client, any workflow.

How It's Different

Most AI tooling answers one of two questions. Memory tools answer *"What does my agent remember?"* Observability tools answer *"What happened in my pipeline?"* Agent Receipts answers a third: "Can you prove it?"

  • Proof, not logs. Every receipt is signed with Ed25519 over every field (format v2). Logs can be edited and are written by the agent about itself; a receipt breaks if anything changes.
  • Anyone can verify it. Offline, in a browser, from the CLI or in code, with a public key. No account, no server, no trusting the person who sent it.
  • History you can't quietly rewrite. Receipts link to the one before them, and verify-chain detects edited, removed or forked receipts.
  • Memory with provenance. Every fact your agent remembers links to the receipt that created it, and can be exported as a bundle someone else can verify.
  • Local-first and free. npx and done. Keys and receipts stay in ~/.agent-receipts. MIT licensed.

What's Inside

  • Automatic receipts — Claude Code hooks (and a plugin) and an MCP proxy that sign every action as it happens
  • 24 MCP tools — memory, actions, verification, constraints, judgments, invoicing, bundles
  • 21 SDK methods — full TypeScript API
  • 17 CLI commands + 9 memory and 3 hooks subcommands — terminal-first
  • 20 dashboard pages — receipts, sessions, memory graph, chains, agents, constraints, judgments, invoices
  • 714 tests (697 across the packages, 17 for the website) — zero TypeScript any in package source
  • Ed25519 + SHA-256 — via @noble/ed25519 (pure JS, no native code); receipt f

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