
Ask Me
io.github.tounsils由 GitHub 帳號 tounsils 發布v0.1.0更新於 Oct 24, 2026
Ask about an operator's work, reusable patterns, availability and offer. Typed tools, eval-gated.
概覽
一個遠端人設伺服器,讓助理回答關於某位營運者的工作、可重用工程模式、檔期與顧問報價的問題。
- 可以做什麼
- 回答關於營運者目前重心、進行中的合作與垂直方向的問題,並附上信心標籤與來源引用。以公開安全的口徑概述具體的過往合作專案。對可重用工程模式目錄做關鍵字檢索。查詢 Playbook 與 Retainer 的剩餘名額及最早可開始日期。取得目前套裝報價的詳細內容。提供預約探索電話的說明與準備指引,但不代為安排時段。
- 適用情境
- 當你希望助理回答關於這位顧問的背景、已交付模式、檔期或報價的問題時適用,例如評估潛在合作或準備預約探索電話。
- 執行需求
- 透過 Streamable HTTP 提供、受 OAuth 2.1 保護的遠端 MCP 端點;清單宣告 OAuth 為必要。需使用支援 OAuth 的用戶端連線,或在用戶端設定中加入端點位址。本機 stdio 開發需要 Node.js 20+ 及儲存庫原始碼。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Ask Me,將其新增到工作區。
- 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
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。
交給代理程式安裝
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/io.github.tounsils%2Fask-me-mcp/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。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。
{
"mcpServers": {
"ask-me": {
"type": "http",
"url": "https://ask-me-mcp-xi.vercel.app/api/mcp"
}
}
}README
ask-me-mcp
A persona MCP server. Ask Claude / ChatGPT / Grok about the operator's work, patterns, availability, and offer — grounded in their public résumé, projects index, and offer page.
Reference implementation of the MCP-Server Harness pattern. This repo is a working example of the same architecture the operator sells as a productized 6-week engagement. If you like the shape, that's the sales pitch — see The pattern at the bottom.
What it does
Six typed tools any AI-assistant user can call:
Every response ships with a confidence label and a source citation. The server never invents; if the grounding data doesn't say it, the server doesn't say it.
Install (as a user)
The remote endpoint speaks MCP Streamable HTTP + OAuth 2.1. Three ways to connect:
1. Claude Desktop — connector directory ("Connect" button)
Add via the Claude Desktop UI: Settings → Connectors → Add custom connector → URL: https://ask-me-mcp-xi.vercel.app/api/mcp. Click Connect. The desktop client discovers OAuth metadata, registers as a client, exchanges tokens, and mounts the tools. No manual config.
2. Claude Desktop / Claude Code — config file (skip OAuth)
Add to claude_desktop_config.json — location varies by OS; see Claude Desktop config docs:
3. Claude Code CLI
Local stdio (development)
For local stdio dev (no HTTP, no OAuth — auth doesn't apply to stdio):
Then in any Claude Code session:
what's Ilyes's current focus? what patterns has he shipped for LLM evaluation? is he available for a Playbook engagement in October?
Develop (as a maintainer)
Requirements
- Node.js 20+
- npm (or pnpm / yarn — package.json is npm-first)
Setup
Run locally as a stdio server
Point Claude Code or the MCP Inspector at the resulting process.
Build for production
Outputs to dist/.
Deploy to Vercel
The api/mcp.ts handler serves the Streamable HTTP transport with OAuth 2.1 protection — the format Claude's connector directory and ChatGPT's Apps SDK both use. See docs/oauth-flow.md for the full architecture.
Run the eval corpus
The tool corpus fails the build if fewer than a threshold percentage of expected answers match. Pass or nothing ships.
The OAuth flow test exercises register → authorize → token → protected /api/mcp → 401 challenge → refresh — all in-process against Vercel-shaped mock req/res objects.
Repository layout
The pattern: the MCP-Server Harness
This project is a reference implementation of a pattern the operator ships to clients as a productized 6-week engagement — the MCP-Server Product Playbook.
The shape:
- Typed tool contract. Six JSON-schema-strict tools. Nothing free-form. The model can only invoke these, only with these arguments.
- Coordinator + specialists (extensible). v0 has one coordinator (the MCP server routing tool calls). v1 will add elicitation + supervisor agents inside more complex tools.
- Typed signal vector. Structured facts extracted from the grounding data. Not free-text.
- Versioned reasoning specification. The tool implementations ARE the reasoning spec — versioned in the code, not in a prompt.
- Rails + confidence. Every response carries
confidence+sources+ optionaldisclaimers. The model can display them. - External grounding. The server queries
src/grounding/data.json; the model never invents. - Evaluation corpus + eval runner + certification.
eval/corpus.jsonhas expected answers;npm run evalreplays them. Ships or doesn't.
If you're building a product that fits this shape (career guidance, medical triage, legal intake, financial planning, coaching, expert-system anything), the operator sells a 6-week fixed-scope engagement to ship it. See get_offer_details or email [email protected].
License
MIT. See LICENSE.
Attribution
Built by Ilyes Tounsi · Carlsbad, CA · tounsils.github.io.
來源:README.md,提交 6c3af7c
工具
0版本歷史
1- v0.1.0最新Sep 16, 2026
評分
已滿足適用檢查項的 85%
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