
Visprobe
io.github.CloudCorpRecords由 GitHub 帳號 CloudCorpRecords 發布v0.1.0更新於 Nov 3, 2026
AI可見性審計:AI爬蟲存取、身份檔案、頁面訊號、託管分析。
AI 翻譯由 AI 模型根據下方的原文描述翻譯,可能有誤。
原文描述
AI-visibility audit: AI crawler access, identity files, page signals, hosted analysis.
概覽
Visprobe 的本機 MCP 服務;無需登入;STDIO。
暫無 AI 概覽:以下資訊來自註冊中心條目和服務本身。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Visprobe,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
visprobe
How does an answer engine see your site? visprobe reads a site
the way one does — the crawler policy in robots.txt, the
identity files an engine looks for, the signals in the page
itself — and, through the hosted analyzer, whether Claude,
ChatGPT, Gemini and Perplexity actually name the site.
Three tools run entirely on your machine; seven forward to the
hosted analyzer at https://inite.ai/api/mcp/analyzer.
Local tools (no account)
check_ai_access(url)— which AI crawlersrobots.txtlets in, split into the answer-engine crawlers (they fetch a page to answer a live question) and the training crawlers. Blocking the first kind is what makes a site invisible; blocking the second costs nothing. The robots rules are applied properly: the most specific user-agent group wins, the longest matching rule wins,Allowbreaks a tie.check_identity_files(url)— which of the ten identity files exist at the site root:/llms.txt,/llms-full.txt,/ai.txt,/ai.json,/identity.json,/agent.json,/.well-known/ai.json,/.well-known/llms.txt,/.well-known/agent.json,/.well-known/ai-plugin.json. A file exists when it is served with a 2xx status.check_page_signals(url)— the page's title, meta description, canonical, hreflang alternates, and the Schema.org types in its JSON-LD.
Remote tools (hosted analyzer)
check_identity(url)— the identity reading with a score out of 100 and what it says to fix. No model asked.visibility_fixes(url)— the fix plan, most important first.compare_sites(url, other)— your site and a competitor's, read the same way, side by side.visibility_history(url)— how the reading moved over time.analyze_site(url)— starts the audit that also asks the answer engines; returns arun_id.get_analysis(run_id)— progress, then the score out of 100 and what to fix first.my_reports()— signed in: your audits, newest first.
Remote calls are forwarded as JSON-RPC tools/call to the
analyzer endpoint. Set INITE_MCP_URL to point at a different
endpoint and INITE_TOKEN to send a Bearer token. Without an
account the open tools answer under a per-address allowance
(two a day, per the upstream service's terms).
CLI
Output is the report as JSON. Exit codes: 0 on success, 1
on a runtime error (including an unreachable site), 2 on a
usage error.
MCP server
MCP client config:
Docker
Development
License
MIT — Copyright (c) 2026 Rene Turcios
來源:README.md,提交 de8fde5
工具
0版本歷史
1- v0.1.0最新Nov 3, 2026
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