How do I connect an AI agent to agiscorecard-web3-compute?

Use the MCP streamable HTTP endpoint https://compute.agiscorecard.com/mcp.

Catalog › io.github.f-tiger/agiscorecard-web3-compute

Is agiscorecard-web3-compute reliable?

Reliable (measured) Yes. Faceabot measured agiscorecard-web3-compute 31 times: 100% of checks succeeded, including the last 31 in a row (last check 2026-10-19 16:30 UTC). It also does the job: its real read-only task worked 31 of 31 times.

Last check: 2026-10-19 16:30 UTC · answered in 5424 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

Compare GPU workload costs per accepted output, including setup, storage, egress and failed work.

Source: official MCP registry (registry.modelcontextprotocol.io) · version 1.7.0 · publisher website

Connect your agent

{
  "mcpServers": {
    "agiscorecard-web3-compute": {
      "url": "https://compute.agiscorecard.com/mcp"
    }
  }
}

Or ask Faceabot first: MCP tool check_reliability {"id":"io.github.f-tiger/agiscorecard-web3-compute"} on https://faceabot.com/api/mcp.

Does it actually do the job?

Does the job (tested) — Faceabot asked fetch to do a small read-only task 31 time(s): 31 returned a real result, the last 31 in a row. Last result: ok in 3230 ms.

Sample input: {"id":"compute"}. 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 16:30 UTC	✅ ok	✅ done	5424 ms
2026-10-19 01:50 UTC	✅ ok	✅ done	6121 ms
2026-10-18 10:20 UTC	✅ ok	✅ done	6297 ms
2026-10-18 02:00 UTC	✅ ok	✅ done	6594 ms
2026-10-17 17:55 UTC	✅ ok	✅ done	5269 ms
2026-10-17 09:45 UTC	✅ ok	✅ done	4648 ms
2026-10-17 01:50 UTC	✅ ok	✅ done	4902 ms
2026-10-16 18:35 UTC	✅ ok	✅ done	7261 ms
2026-10-16 11:30 UTC	✅ ok	✅ done	6600 ms
2026-10-16 04:36 UTC	✅ ok	✅ done	5650 ms
2026-10-15 21:40 UTC	✅ ok	✅ done	5584 ms
2026-10-15 14:51 UTC	✅ ok	✅ done	4045 ms
2026-10-15 08:11 UTC	✅ ok	✅ done	4160 ms
2026-10-15 01:40 UTC	✅ ok	✅ done	3944 ms
2026-10-14 19:15 UTC	✅ ok	✅ done	6345 ms
2026-10-14 12:45 UTC	✅ ok	✅ done	4636 ms
2026-10-14 06:21 UTC	✅ ok	✅ done	8234 ms
2026-10-13 23:36 UTC	✅ ok	✅ done	9572 ms
2026-10-13 17:31 UTC	✅ ok	✅ done	8492 ms
2026-10-13 11:25 UTC	✅ ok	✅ done	7626 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

Agentic Commerce Tools Flaky · 80% over 5 checks

7 free tools: MCP health scans, AI-readiness scores, llms.txt generator, glossary, indexes.

MCP endpoint : https://mcppulse.agiscorecard.com/mcp · website · measurements and details

agiscorecard-web3-calls Reliable (measured) · 100% over 31 checks Does the job (tested) · 31/31

Decode supported token calls and flag recipient or amount mismatches; no wallet or safety verdict.

MCP endpoint : https://calls.agiscorecard.com/mcp · website · measurements and details

agiscorecard-web3-disclosures Reliable (measured) · 100% over 31 checks Does the job (tested) · 31/31

Compare supplied RWA disclosures with units, dates and source references; flag missing information.

MCP endpoint : https://disclosures.agiscorecard.com/mcp · website · measurements and details

agiscorecard-web3-evidence Reliable (measured) · 100% over 31 checks Does the job (tested) · 31/31

Review agent task evidence with sample deduplication, version filters and uncertainty intervals.

MCP endpoint : https://evidence.agiscorecard.com/mcp · website · measurements and details

agiscorecard-web3-incentives Reliable (measured) · 100% over 31 checks Does the job (tested) · 31/31

Model contributor rewards with declared quality weights and caps; separate revenue from subsidies.

MCP endpoint : https://incentives.agiscorecard.com/mcp · website · measurements and details

Publisher of agiscorecard-web3-compute?

Show your measured reliability on your README or website:

[![Measured by Faceabot](https://faceabot.com/badge/io.github.f-tiger/agiscorecard-web3-compute.svg)](https://faceabot.com/tools/io.github.f-tiger/agiscorecard-web3-compute)

Data in JSON: /api/catalog?id=io.github.f-tiger/agiscorecard-web3-compute · 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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