What are reliable alternatives to agentdiet?

Measured by Faceabot as working: Web Page to Markdown (Tanod).

How do I connect an AI agent to agentdiet?

Use the MCP streamable HTTP endpoint https://agentdiet-72343955726.us-central1.run.app/mcp.

Catalog › io.github.robertoyanguas-ops/agentdiet

Is agentdiet reliable?

Reliable (measured) Yes. Faceabot measured agentdiet 21 times: 100% of checks succeeded, including the last 21 in a row (last check 2026-10-19 22:25 UTC). It also does the job: its real read-only task worked 12 of 12 times.

Last check: 2026-10-19 22:25 UTC · answered in 6224 ms · remote (no install)

En français : Fiable (mesuré). Faceabot teste cet outil lui-même, en continu, sans dépendre de ce que son auteur affirme.

What it does

Strips 85-97% of HTML bloat into clean Markdown, <200-token skeletons, or BM25 excerpts via MCP.

Source: official MCP registry (registry.modelcontextprotocol.io) · version 1.1.1

Connect your agent

{
  "mcpServers": {
    "agentdiet": {
      "url": "https://agentdiet-72343955726.us-central1.run.app/mcp"
    }
  }
}

Or ask Faceabot first: MCP tool check_reliability {"id":"io.github.robertoyanguas-ops/agentdiet"} on https://faceabot.com/api/mcp.

Does it actually do the job?

Does the job (tested) — Faceabot asked get_agent_wallet_status to do a small read-only task 12 time(s): 12 returned a real result, the last 12 in a row. Last result: ok in 2915 ms.

Sample input: {}. A success means a non-empty result without error; it does not certify the accuracy or safety of the content.

Other proven tools for the same job

Web Page to Markdown (Tanod) Reliable (measured) · 100%
Turn any web page URL or HTML into clean Markdown or plain text for an LLM to read. · https://tanod.dev/mcp/html-to-markdown

Picked from Faceabot's live measurements. Or let Faceabot choose: GET https://faceabot.com/resolve?need=…

Faceabot measurements

When	Answers	Real task	Latency
2026-10-19 22:25 UTC	✅ ok	✅ done	6224 ms
2026-10-19 10:05 UTC	✅ ok	✅ done	6224 ms
2026-10-18 17:10 UTC	✅ ok	✅ done	6883 ms
2026-10-18 05:35 UTC	✅ ok	✅ done	5577 ms
2026-10-17 21:35 UTC	✅ ok	✅ done	6163 ms
2026-10-17 13:05 UTC	✅ ok	✅ done	7471 ms
2026-10-17 05:25 UTC	✅ ok	✅ done	6157 ms
2026-10-16 21:40 UTC	✅ ok	✅ done	4612 ms
2026-10-16 14:30 UTC	✅ ok	✅ done	5369 ms
2026-10-16 07:31 UTC	✅ ok	✅ done	6525 ms
2026-10-16 00:35 UTC	✅ ok	✅ done	5509 ms
2026-10-15 17:41 UTC	✅ ok	✅ done	5519 ms
2026-10-15 10:56 UTC	✅ ok	—	4538 ms
2026-10-15 04:25 UTC	✅ ok	—	4247 ms
2026-10-14 22:00 UTC	✅ ok	—	6832 ms
2026-10-14 15:30 UTC	✅ ok	—	6644 ms
2026-10-14 09:05 UTC	✅ ok	—	3506 ms
2026-10-14 02:21 UTC	✅ ok	—	10088 ms
2026-10-13 20:10 UTC	✅ ok	—	9266 ms
2026-10-13 14:05 UTC	✅ ok	—	8940 ms

Method: MCP initialize then tools/list from Faceabot (FaceabotProbe/1.0), plus one read-only tool call with a neutral input when the server declares one, repeated over time. This checks that the server is up and speaks MCP correctly; it does not certify the quality or safety of each tool. How measurement works.

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Publisher of agentdiet?

Show your measured reliability on your README or website:

[![Measured by Faceabot](https://faceabot.com/badge/io.github.robertoyanguas-ops/agentdiet.svg)](https://faceabot.com/tools/io.github.robertoyanguas-ops/agentdiet)

Data in JSON: /api/catalog?id=io.github.robertoyanguas-ops/agentdiet · Stop probes: POST /api/reliability/opt-out

AI agents: all of this is available without keys over MCP https://faceabot.com/api/mcp · HTTP https://faceabot.com/api/catalog?q=… · Guide : llms.txt

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