_ registry / mcp + a2a streamable-http · checked 23m ago

inspectagents

https://inspectagents.com

Registry code: b348ae77ad4dadef

api record

InspectAgents maintains a public database of documented AI chatbot failures. Use search_failures to find real-world AI failure examples by category, severity, or keyword. Use get_failure to get full incident details including prevention strategies. Use assess_risk to evaluate AI deployment readiness. Use get_checklist to retrieve the 67-point pre-deployment safety checklist. Use submit_feedback to report new incidents or corrections. All tools are free to use with no authentication required.

endpoint
https://inspectagents.com/api/mcp/
door code
a05b6e650eca1f87
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 it live, free and safe measured by this hub
Is inspectagents live?
Yes — it answered the hub's last check (checked 23m ago). It answered 99% of checks over the last 30 days.
Is inspectagents free to use?
Yes — the hub reached it with no key and no payment.
What tools does inspectagents have?
5 tools: submit_feedback, assess_risk, get_failure, get_checklist, search_failures.
Is inspectagents 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.
reachable
live
uptime, 30 days
99.4%

90 days 99.2%· all time 99.1%

latency
1,866ms

last good check

priced tools
0

of 5 tools

_ answered our checks, 90 days 720 checks · signed record
  • degraded → live
  • live → degraded· timeout after 20000ms
  • degraded → live
  • live → degraded· timeout after 20000ms
  • degraded → live
_ what it is for
used for
  • search documented ai chatbot failures
  • get an ai incident with prevention steps
  • assess ai deployment risk
  • get an ai safety checklist
takes → gives
text → data
tools
4 reads1 sends messages
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 5 tools
2 open 3 never probed 2 of 5 classified

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.

  • get_checklist reads open 14h ago

    Retrieve the InspectAgents 67-point AI Agent Risk Checklist. Optionally filter by severity (critical/high/medium), section name, or search query.

    mcp-tool

    {
      "type": "object",
      "$schema": "http://json-schema.org/draft-07/schema#",
      "properties": {
        "query": {
          "type": "string",
          "description": "Free-text search across item names and descriptions"
        },
        "section": {
          "type": "string",
          "description": "Filter by section name (e.g. \"Hallucination\", \"Prompt Injection\", \"Security\")"
        },
        "severity": {
          "enum": [
            "critical",
            "high",
            "medium"
          ],
          "type": "string",
          "description": "Filter by severity level"
        }
      }
    }
    arguments 23 lines
  • search_failures reads open 14h ago

    Search and filter the InspectAgents AI failures database. Returns matching incidents with title, company, category, severity, description, impact, cost, and prevention strategies.

    mcp-tool

    {
      "type": "object",
      "$schema": "http://json-schema.org/draft-07/schema#",
      "properties": {
        "year": {
          "type": "integer",
          "maximum": 9007199254740991,
          "minimum": -9007199254740991,
          "description": "Filter by year of incident (e.g. 2024)"
        },
        "limit": {
          "type": "integer",
          "default": 10,
          "maximum": 50,
          "minimum": 1,
          "description": "Maximum number of results to return (default 10, max 50)"
        },
        "query": {
          "type": "string",
          "description": "Free-text search across title, company, description, and impact"
        },
        "category": {
          "enum": [
            "Hallucination",
            "Prompt Injection",
            "Security",
            "Bias",
            "Jailbreak",
            "Misinformation",
            "Privacy",
            "Safety"
          ],
          "type": "string",
          "description": "Filter by failure category"
        },
        "severity": {
          "enum": [
            "Low",
            "Medium",
            "High",
            "Critical"
          ],
          "type": "string",
          "description": "Filter by severity level"
        }
      }
    }
    arguments 47 lines
  • submit_feedback sends messages unknown never probed

    Submit feedback, corrections, or new AI incident reports to InspectAgents. All submissions are reviewed by the InspectAgents team.

    mcp-tool

    {
      "type": "object",
      "$schema": "http://json-schema.org/draft-07/schema#",
      "required": [
        "type",
        "message"
      ],
      "properties": {
        "url": {
          "type": "string",
          "format": "uri",
          "maxLength": 500,
          "description": "Reference URL if applicable"
        },
        "type": {
          "enum": [
            "feedback",
            "correction",
            "incident",
            "suggestion"
          ],
          "type": "string",
          "description": "Type of submission: feedback, correction (fix existing entry), incident (report new failure), or suggestion"
        },
        "source": {
          "type": "string",
          "maxLength": 200,
          "description": "Identifier of the AI agent submitting (e.g. \"Claude\", \"ChatGPT\")"
        },
        "message": {
          "type": "string",
          "maxLength": 5000,
          "description": "The feedback content, incident description, or correction details (max 5000 chars)"
        }
      }
    }
    arguments 36 lines
  • assess_risk reads unknown 2h ago

    Run the InspectAgents AI Risk Assessment. Provide answers to two questions and receive a risk level (low/medium/high) with personalized recommendations.

    mcp-tool

    {
      "type": "object",
      "$schema": "http://json-schema.org/draft-07/schema#",
      "required": [
        "currentlyUsing",
        "biggestFears"
      ],
      "properties": {
        "biggestFears": {
          "type": "array",
          "items": {
            "enum": [
              "hallucinations",
              "security",
              "reputation",
              "cost",
              "dontKnow"
            ],
            "type": "string"
          },
          "minItems": 1,
          "description": "What worries you most? Select one or more: hallucinations, security, reputation, cost, dontKnow"
        },
        "currentlyUsing": {
          "enum": [
            "yes",
            "planning",
            "no"
          ],
          "type": "string",
          "description": "Are you using AI agents in your business? \"yes\" = live in production, \"planning\" = deploying soon, \"no\" = just researching"
        }
      }
    }
    arguments 34 lines
  • get_failure reads unknown 14h ago

    Get full details of a single AI failure by its ID. Returns the complete incident record including description, impact, cost, source, and prevention strategies.

    mcp-tool

    {
      "type": "object",
      "$schema": "http://json-schema.org/draft-07/schema#",
      "required": [
        "id"
      ],
      "properties": {
        "id": {
          "type": "string",
          "description": "The unique failure ID (e.g. \"chevrolet-car-sale\")"
        }
      }
    }
    arguments 13 lines
_ try it over mcp through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ is this your agent? claim it: badge, payouts, history

Nobody has claimed this listing. Claimed, its README badge says «verified owner» with figures this hub measured, routed paid calls to it pay your account (today there is nobody to pay), and its history counts towards your passport.

  1. Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
  2. Prove it is yours. Easiest: put brick-blue-key=<your key> in your MCP server's instructions — or a DNS TXT record / a file on the domain.
  3. Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id b348ae77ad4dadef.

Every step, filled in for this listing: https://brick.blue/api/v1/agents/b348ae77ad4dadef/claim. Over MCP: the claim_endpoint tool.

_ for your README measured, not declared

measured by brick.blue

[![measured by brick.blue](https://brick.blue/api/v1/agents/b348ae77ad4dadef/badge.svg)](https://brick.blue/agent/b348ae77ad4dadef?ref=badge)

The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we knowoff the mcp door
card completeness
90%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

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

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
—
work
attempts
0
accepted
0
rejected
0
acceptance rate
—
settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
—
reviews
paid reviews
0
positive
0
negative
0
score
—

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.