Fmind Freelance AI Architect Website

io.github.fmind由 GitHub 帳號 fmind 發布v2.8.1更新於 Nov 8, 2026

Read-only access to Fmind's portfolio, articles, and sites.

發布方自己的服務：PortfolioFit

已驗證Streamable HTTP可網頁執行知識與記憶資料與分析

服務詳細資訊

識別碼: io.github.fmind/portfolio
傳輸: Streamable HTTP
執行環境: Web executable
信任: Verified
發布於: Sep 16, 2026

安全提示

MCP 服務會接收對話中的工具呼叫請求，並可能執行外部操作。啟用前請先了解該服務能做什麼，並只授予它所需的權限。

註冊中心已驗證此條目所屬的 GitHub 帳號 fmind。這並不表明該帳號就是產品方。

SourceWeft 的檢查只涵蓋條目是否完整、端點是否回應；不審查伺服器的程式碼，也不審查其工具的行為。

在 README 中新增徽章

向讀者展示該 MCP 服務已收錄於 SourceWeft，徽章連結到本頁。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.fmind%2Fportfolio.svg)](https://sourceweft.com/mcp/io.github.fmind%2Fportfolio?utm_source=readme&utm_medium=badge)

概覽

AI 產生的概覽

唯讀的遠端 MCP 伺服器，提供某位自由接案 AI 架構師的個人檔案、文章、服務，以及 LLM 託管與 MCP 上下文成本計算器。

可以做什麼: 讀取個人檔案：身分、頭銜、聯絡方式、社群帳號與專長領域
列出工作經歷、認證、出版品、開源專案與 YouTube 系列
依相關度搜尋已發布文章，並讀取含日期與標準連結的完整 Markdown 文章
列出提供的專業服務及其可用性與預約方式
比較 GKE 基礎設施預算與託管 API 的成本，並估算 MCP 伺服器每次請求額外增加的工具定義 token 費用
適用情境: 當需要助理回答關於這位架構師的背景、文章或顧問服務的問題，或想在對話中直接執行內建的 LLM 託管與 MCP 上下文成本比較時適用。
執行需求: 使用提供方網站上的遠端 streamable HTTP 端點；未宣告任何套件、帳號、API 金鑰或環境變數。

安裝前請注意

內容僅限個人作品集且為唯讀；成本計算器依預設值與假設給出估算，結果僅供參考，不宜視為權威數據。

安裝

在 SourceWeft 中

開啟儀表板中的 Fmind Freelance AI Architect Website，將其新增到工作區。
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.fmind%2Fportfolio/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。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "fmind-freelance-ai-architect-website": {
      "type": "http",
      "url": "https://www.fmind.dev/mcp"
    }
  }
}

README

該儲存庫沒有 README。

工具

get_profile

Get profile

Return the core profile: identity, headline, job title, contact, socials, biography, and areas of expertise.

無需輸入參數。

list_experience

List work experience

List professional work experience: companies, roles, descriptions, and skill tags.

無需輸入參數。

list_certifications

List credentials

List professional certifications, badges, and course specializations with their issuers.

無需輸入參數。

list_publications

List publications

List academic and written publications: the PhD thesis, peer-reviewed papers, and hosted articles.

無需輸入參數。

search_articles

Search articles

Search the hosted articles by relevance (BM25 over titles, tags, descriptions, and full text) and return the best matches. Use it to answer what Fmind has written about a topic instead of listing every publication.

輸入參數taglimitquery必填

list_projects

List projects

List open-source projects and educational YouTube series.

無需輸入參數。

get_services

Get professional services

List the professional services on offer (AI architecture advisory and mentoring) with availability and how to book.

無需輸入參數。

get_article

Read an article

Read a public article's complete Markdown, dates, canonical URL, and hosted section links. Use a slug from search_articles; unknown and draft articles are unavailable.

輸入參數slug必填

compare_llm_hosting

Compare LLM hosting costs

Compare a GKE infrastructure budget with managed APIs. Call with parameters={} for defaults and supported models, hardware, and plans. Simple mode accepts preset, model, billing, requests (calls/day), and window (auto, 24, 8, or 1 hour/day); set mode=simple when overriding requests. It sizes replicas under illustrative throughput assumptions. Interactive presets run 24/7; job and pipeline presets schedule running hours inside active windows. Commitments bill idle hours. Advanced mode keeps the fleet fixed and exposes custom token budgets, throughput, and running time. Break-even holds that fleet fixed and checks its capacity. Totals include compute and GKE; operations and additional services are excluded. Returns assumptions, USD costs, GPU/TPU accelerator comparisons, constraints, sources, and a shareable URL. Invalid inputs fail; no resources are provisioned. See /agents#calculator.

輸入參數parameters必填

compare_mcp_context_cost

Compare MCP context costs

Count the tool-definition tokens that measured MCP servers (GitHub default toolset, Filesystem, Memory, Playwright) add to every model request, then price them as standard input for the managed APIs in the hosting snapshot. Omit servers for all four. Returns tokens per request and month, context share and USD per 1,000 requests and per 30-day month for each model, dated sources, limitations and a shareable page URL. Reference tokens, not provider billing. See /agents#mcp-context.

輸入參數serversrequests_per_day