ai.agentblueprint由 agentblueprint.ai 發布官方發布者v0.2.0更新於 Nov 3, 2026
可測量代理成本、一頁式代理摘要檢查以及離線存取地圖。無需登入。
AI 翻譯由 AI 模型根據下方的原文描述翻譯，可能有誤。
Measured agent costs, a one-page agent summary check, and an offline access map. No sign-in.
Agent Blueprint 的託管 MCP 服務（agentblueprint.ai），由 agentblueprint.ai 發布；無需登入；Streamable HTTP；4 個工具。
暫無 AI 概覽：以下資訊來自註冊中心條目和服務本身。
Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式，或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南，先向你展示發布者、端點和登入方式，經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/ai.agentblueprint%2Fagent-blueprint/install.md，並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前，先告訴我它的發布者、端點和登入方式，等我確認。不要把 API 金鑰寫進命令或我會提交的檔案；問我金鑰應從哪裡取得。把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"agent-blueprint": {
"type": "http",
"url": "https://agentblueprint.ai/mcp"
}
}
}This is a Next.js project bootstrapped with create-next-app.
First, run the development server:
Open http://localhost:3000 with your browser to see the result.
You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.
This project uses next/font to automatically optimize and load Geist, a new font family for Vercel.
To learn more about Next.js, take a look at the following resources:
You can check out the Next.js GitHub repository - your feedback and contributions are welcome!
The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.
Check out our Next.js deployment documentation for more details.
來源：README.md，提交 0b4b3db
List measured agent jobs
Lists the ten everyday jobs in Agent Blueprint's measured agent cost benchmark (2 November 2026): what each job was, how big its input was, and the typical and worst-case tokens and dollar cost measured over five runs each on Claude Code and Codex. Use it to find the benchmark job closest to a task someone wants an agent to do, before estimating that task's cost.
agentEstimate an agent task's cost
Estimates the tokens and dollar cost of an AI agent task from the measured benchmark job closest to it. For jobs where cost grows with how much the agent reads, give the size of the real input and it scales the reading part while keeping the agent's fixed overhead. Returns a typical and a budget (worst-case) figure per run and, if runs per month are given, per month. Uses the benchmark-day prices unless current prices are passed. The result is an estimate from small test jobs, not a quote.
job必填agent必填pricesyour_sizeruns_per_monthCheck a one-page agent summary
Checks the structure of a one-page agent summary written from Agent Blueprint's template (https://agentblueprint.ai/agent-one-page-template): all eight sections present and in order, a stage line, every rule ending in "Enforced by:" or "Not enforced:", every Open item naming who decides, no template placeholders left, and length within one page. It checks shape only, not whether the answers are right. The text is checked and returned findings only; it is not stored.
markdown必填Draw an agent's access map
Turns an agent's own inventory of its connections into Agent Blueprint's one-page access map: a single offline HTML page showing what the agent can read and change, who has to approve, its riskiest powers, and what could be trimmed. The agent supplies the inventory from its own tool list; this tool only draws it. Returns the HTML for the person to save, such as my-agent-blueprint.html. The inventory is not stored. The field guide is at https://agentblueprint.ai/draw.md.
trim必填agent必填drawn必填checks必填unseen必填version必填connections必填已滿足適用檢查項的 90%
該評分衡量此收錄條目的完整程度，依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價，也不表示伺服器安全或目前可用：可連通性是帶日期的檢查結果，評分也不包含安裝量或使用者評價。
請在儲存庫或註冊中心條目中宣告授權條款。
由 GitHub 帳號 agent-blueprint 發布
Client teams' blueprints for coding agents (token from an engagement). Free: agentblueprint.ai/mcp
由 GitHub 帳號 agent-blueprint 發布
Two sample multi-agent blueprints over MCP, no signup. Main server: agentblueprint.ai/mcp
npm run dev# oryarn dev# orpnpm dev# orbun dev