https://dag-studio-webmcp-bridge.jdiazdecaro.workers.dev/mcp ↗
Read and edit a live DAG Studio canvas through its predefined WebMCP tools.
DAG Studio WebMCP is a remote MCP server published at dag-studio-webmcp-bridge.jdiazdecaro.workers.dev. It has been probed 10 times since 9/12/2026. It answered in 10 of them (100.0%), a near-uninterrupted record. Median response time is 1,460 ms, a delay an agent will notice. Its tool list could not be read; the server is closed to direct calls. It answers direct calls with an authentication wall.
Can an LLM agent pick the right tool here — names, descriptions and parameter clarity are assessed.
| Run | Era | Modern | ms | Legacy | ms | Versions |
|---|---|---|---|---|---|---|
| 2026-09-13 10:45:14 | Auth-gated | 401 | 1884 | 401 | 1867 | — |
| 2026-09-13 08:43:04 | Auth-gated | 401 | 1124 | 401 | 1165 | — |
| 2026-09-13 06:40:42 | Auth-gated | 401 | 933 | 401 | 869 | — |
| 2026-09-13 04:35:29 | Auth-gated | 401 | 1525 | 401 | 1521 | — |
| 2026-09-13 01:33:33 | Auth-gated | 401 | 1387 | 401 | 1371 | — |
| 2026-09-12 23:31:36 | Auth-gated | 401 | 1216 | 401 | 1214 | — |
| 2026-09-12 21:29:15 | Auth-gated | 401 | 1053 | 401 | 1007 | — |
| 2026-09-12 19:27:29 | Auth-gated | 401 | 1472 | 401 | 1460 | — |
| 2026-09-12 17:24:09 | Auth-gated | 401 | 1681 | 401 | 1690 | — |
| 2026-09-12 15:21:42 | Auth-gated | 401 | 1543 | 401 | 1541 | — |
Each block is one measurement round. Green: working response. Amber: responded but the server was returning errors (5xx). Red: no response at all.
Each cell is one probe run. Faded cells are incomplete probes — one leg did not answer, so the era is inconclusive.
The two probe legs separately: modern server/discover and legacy initialize.
Derived by comparing consecutive probes — changes in era, protocol version, build and reachability.
Add this badge to your README — it updates automatically as measurements change.
[](https://mcpmetrics.io/servers/io-github-black-swan-causal-labs-dag-studio-webmcp)<a href="https://mcpmetrics.io/servers/io-github-black-swan-causal-labs-dag-studio-webmcp"><img src="https://mcpmetrics.io/badge/io.github.Black-Swan-Causal-Labs/dag-studio-webmcp/era.svg" alt="mcpmetrics"></a>You are seeing the last 7 days. Sign up for the full history. Which check failed and why is in the dashboard.
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Read and edit a live study design canvas through its predefined WebMCP tools.
Brand audits, visual catalogs, AI proposals & checkout for LATAM SMBs. Full funnel via MCP.
Yapp turns "build me a page and publish it" into a live URL. Connect once (browser OAuth, or a token for terminal clients) and your AI can publish a webpage from HTML, or host a PDF, image, or ZIP exactly as-is to a public `<slug>.yapp.page` URL in seconds, then update, password-protect, set expiry, attach a custom domain, or read form submissions, all by asking. Free to start; no local install. **Tools (15):** `publish_page`, `publish_file`, `update_page`, `delete_page`, `get_page_stats`, `list_my_pages`, `rename_page`, `change_page_slug`, `set_page_expiry`, `set_page_password`, `list_submissions`, `add_custom_domain`, `list_custom_domains`, `check_custom_domain`, `remove_custom_domain`.
ABC sheet music + Strudel live coding studio with ext-apps widgets, harmony tools, and share links.
Search, compare and read reviews of 350+ homeschool curricula. Read-only, no account needed.
gemini-extension.json n'est pas un mécanisme d'auto-discovery. Les Gemini Extensions sont publiées via Google AI Studio / Extensions Gallery, pas via crawl du .well-known/. Ton fichier est invisible pour Gemini. 3. ChatGPT ai-plugin.json correspond à la spec OpenAI Plugins, dépréciée en 2024. Remplacée par les GPTs (publiés via GPT Store) et les Actions (configurées dans un GPT custom). Ton fichier est mort techniquement. 4. llms.txt Proposition de standard (llmstxt.org). Aucun éditeur de LLM (Anthropic, OpenAI, Google) n'a confirmé crawler ce fichier. C'est un pari sur l'avenir, pas une réalité opérationnelle. 5. MCP endpoint Il existe, il est valide, mais aucun LLM ne le trouve tout seul. Il faut l'inscrire manuellement dans le client de l'utilisateur. Ce qui marche réellement aujourd'hui Quand un LLM répond à une question sur Timers Studio, il utilise : 1. Sa donnée d'entraînement (figée) 2. Un WebFetch live sur les pages publiques timers.st
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