How do I connect an AI agent to AI Footprint?

Use the MCP streamable HTTP endpoint https://footprint.pharmatools.ai/mcp.

Catalog › io.github.nickjlamb/ai-footprint

Is AI Footprint reliable?

Reliable (measured) Yes. Faceabot measured AI Footprint 27 times: 100% of checks succeeded, including the last 27 in a row (last check 2026-10-19 15:40 UTC). It also does the job: its real read-only task worked 27 of 27 times.

Last check: 2026-10-19 15:40 UTC · answered in 9761 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

Water and energy footprint of AI use: chat prompts, agent sessions, methodology and sources.

Source: official MCP registry (registry.modelcontextprotocol.io) · version 1.0.4 · publisher website

Connect your agent

{
  "mcpServers": {
    "ai-footprint": {
      "url": "https://footprint.pharmatools.ai/mcp"
    }
  }
}

Or ask Faceabot first: MCP tool check_reliability {"id":"io.github.nickjlamb/ai-footprint"} on https://faceabot.com/api/mcp.

Does it actually do the job?

Does the job (tested) — Faceabot asked get_methodology to do a small read-only task 27 time(s): 27 returned a real result, the last 27 in a row. Last result: ok in 2994 ms.

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

Faceabot measurements

When	Answers	Real task	Latency
2026-10-19 15:40 UTC	✅ ok	✅ done	9761 ms
2026-10-19 00:40 UTC	✅ ok	✅ done	6029 ms
2026-10-18 09:25 UTC	✅ ok	✅ done	7321 ms
2026-10-18 01:35 UTC	✅ ok	✅ done	4404 ms
2026-10-17 17:25 UTC	✅ ok	✅ done	4541 ms
2026-10-17 09:20 UTC	✅ ok	✅ done	4075 ms
2026-10-17 01:20 UTC	✅ ok	✅ done	6005 ms
2026-10-16 18:10 UTC	✅ ok	✅ done	5870 ms
2026-10-16 11:05 UTC	✅ ok	✅ done	5977 ms
2026-10-16 04:10 UTC	✅ ok	✅ done	4167 ms
2026-10-15 21:15 UTC	✅ ok	✅ done	4212 ms
2026-10-15 14:21 UTC	✅ ok	✅ done	5220 ms
2026-10-15 07:45 UTC	✅ ok	✅ done	1784 ms
2026-10-15 01:10 UTC	✅ ok	✅ done	4023 ms
2026-10-14 18:45 UTC	✅ ok	✅ done	6860 ms
2026-10-14 12:15 UTC	✅ ok	✅ done	5843 ms
2026-10-14 05:51 UTC	✅ ok	✅ done	8669 ms
2026-10-13 23:01 UTC	✅ ok	✅ done	7442 ms
2026-10-13 16:55 UTC	✅ ok	✅ done	6085 ms
2026-10-13 10:46 UTC	✅ ok	✅ done	6746 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.

More from the same publisher

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Package npm : @pharmatools/groundwork · website · measurements and details

opengate-mcp Not measured yet

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Package npm : @pharmatools/opengate-mcp · website · measurements and details

pubcrawl Not measured yet

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Package npm : @pharmatools/pubcrawl · website · measurements and details

redacta-mcp Not measured yet

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Package npm : redacta-mcp · website · measurements and details

studydiff Not measured yet

Explain why two scientific papers disagree, every claim grounded in a verbatim source quote.

Package npm : studydiff-mcp · website · measurements and details

Find tools similar to AI Footprint →

Publisher of AI Footprint?

Show your measured reliability on your README or website:

[![Measured by Faceabot](https://faceabot.com/badge/io.github.nickjlamb/ai-footprint.svg)](https://faceabot.com/tools/io.github.nickjlamb/ai-footprint)

Data in JSON: /api/catalog?id=io.github.nickjlamb/ai-footprint · 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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