What are reliable alternatives to agiscorecard-web3-protocol?

Measured by Faceabot as working: ERC-8126 Scan, NullClear Arbiter, Fuci.

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

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

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

Is agiscorecard-web3-protocol reliable?

Reliable (measured) Yes. Faceabot measured agiscorecard-web3-protocol 31 times: 100% of checks succeeded, including the last 31 in a row (last check 2026-10-19 17:45 UTC). It also does the job: its real read-only task worked 31 of 31 times.

Last check: 2026-10-19 17:45 UTC · answered in 7035 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

Read dated x402, ERC-8004 and token-interface profiles with official sources and freshness limits.

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

Connect your agent

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

Or ask Faceabot first: MCP tool check_reliability {"id":"io.github.f-tiger/agiscorecard-web3-protocol"} 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 1215 ms.

Sample input: {"id":"protocol"}. 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

ERC-8126 Scan Reliable (measured) · 100%
378k+ ERC-8004 agents and their security verifications. Two tools free, the rest USDC over x402. · https://erc8126scan.ai/api/mcp

NullClear Arbiter Reliable (measured) · 100%
Autonomous x402 payment schema-escrow arbiter, spend firewall, failover & ERC-8004 Sybil oracle · https://api.nullclear.dev/mcp

Fuci Flaky · 88%
AI agents on Arc: search paid x402 APIs, ERC-8004 reputation, Argus launch data paid in USDC. · https://www.fuci.family/api/mcp

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 17:45 UTC	✅ ok	✅ done	7035 ms
2026-10-19 03:35 UTC	✅ ok	✅ done	5078 ms
2026-10-18 11:45 UTC	✅ ok	✅ done	4982 ms
2026-10-18 02:45 UTC	✅ ok	✅ done	4623 ms
2026-10-17 18:45 UTC	✅ ok	✅ done	5102 ms
2026-10-17 10:25 UTC	✅ ok	✅ done	5938 ms
2026-10-17 02:40 UTC	✅ ok	✅ done	6577 ms
2026-10-16 19:05 UTC	✅ ok	✅ done	8616 ms
2026-10-16 12:02 UTC	✅ ok	✅ done	6725 ms
2026-10-16 05:05 UTC	✅ ok	✅ done	4651 ms
2026-10-15 22:10 UTC	✅ ok	✅ done	3770 ms
2026-10-15 15:16 UTC	✅ ok	✅ done	4513 ms
2026-10-15 08:31 UTC	✅ ok	✅ done	4754 ms
2026-10-15 02:05 UTC	✅ ok	✅ done	2681 ms
2026-10-14 19:40 UTC	✅ ok	✅ done	5109 ms
2026-10-14 13:10 UTC	✅ ok	✅ done	3879 ms
2026-10-14 06:46 UTC	✅ ok	✅ done	5827 ms
2026-10-13 23:56 UTC	✅ ok	✅ done	7649 ms
2026-10-13 17:50 UTC	✅ ok	✅ done	7663 ms
2026-10-13 11:46 UTC	✅ ok	✅ done	9816 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-compute Reliable (measured) · 100% over 31 checks Does the job (tested) · 31/31

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

MCP endpoint : https://compute.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

Publisher of agiscorecard-web3-protocol?

Show your measured reliability on your README or website:

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

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