trustai-verify

endpoint

https://trustailaw.com/api/mcp

protocol

streamable-http ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing · is it yours? claim it

karma

0 · newcomer

Is trustai-verify live?

Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.

Is trustai-verify free to use?

Yes — the hub reached it with no key and no payment.

What tools does trustai-verify have?

4 tools: review_legal_text, list_checks, get_descriptor, get_health.

Is trustai-verify safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• list_checks reads open 13h ago

  Return the structural checks this server performs on legal-AI output, and — explicitly — what it never claims. Information, not legal advice.

  mcp-tool

  12345

  {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }

  arguments 5 lines copy
• get_descriptor reads open 13h ago

  Return the TrustAI Verification MCP self-description: operator, what the server verifies, the public tools, the boundary it never crosses (it never adjudicates), and links to the public surfaces.

  mcp-tool

  12345

  {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }

  arguments 5 lines copy
• get_health reads open 13h ago

  Return server health: process uptime and a deterministic engine self-check (the structural detectors run on a fixed sample and return the expected flag counts). Local-only; no database on the path.

  mcp-tool

  12345

  {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }

  arguments 5 lines copy
• review_legal_text reads unknown 21h ago

  Independently review legal text produced by ANY AI vendor for the structural red-flags behind fabrication risk: (1) orphan quotations — a quoted span with no citation in its sentence, the citation sentence after it, or its footnote; (2) uncited propositions — law stated as established (a holding cue or a settled-law phrase such as 'it is well established') with no such citation; (3) court mismatch — the text names one circuit, the cite another; (4) impossible date — a citation year in the future or before its reporter series began; (5) court/reporter mismatch — a court and reporter that cannot both be right; (6) a case name and cite matching one publicly identified as non-existent in Mata v. Avianca (S.D.N.Y. 2023). Recognizes full and short-form cites (Id., supra, Westlaw/Lexis, U.S.C., C.F.R., state codes, court rules) and footnotes; triggers in English and Spanish. Returns each flag with the exact passage, its offsets, a severity and a plain structural observation, FOR YOUR REVIEW. It is a neutral referee: it never tells you the answer is right or wrong, never adjudicates, and abstains (returns no flags) on any fault rather than fabricating one. Deterministic and local — no external lookup. (Live case-citation existence checking against CourtListener runs on the website verifier at /verify; multi-model cross-validation runs in TrustAI's document-analysis engine and the licensed pilot — neither runs on this load-safe tool.)

  mcp-tool

  12345678910111213

  {
    "type": "object",
    "required": [
      "text"
    ],
    "properties": {
      "text": {
        "type": "string",
        "description": "The legal text to review (a memo, brief, or answer from any AI vendor). Max 200000 chars."
      }
    },
    "additionalProperties": false
  }

  arguments 13 lines copy

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.