Verify-api

verify_ai_claim

Read-onlyIdempotent

Verify whether an AI model, API provider, pricing claim, or infrastructure assertion is true today using live web evidence. Returns deterministic verdicts (TRUE, FALSE, PARTIALLY_TRUE, UNREACHABLE, UNVERIFIED) with cited sources and confidence scores. Requires x402 micropayment (0.01 USDC on Base).

When to use: Fact-checking an AI provider's claims, pricing, or model availability. When NOT to use: Do NOT use for general open-ended web search, coding assistance, or non-AI claim verification.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`depth`	No	Verification depth: 'standard' (0.01 USDC) or 'deep' (0.03 USDC).	standard
`query`	Yes	The specific AI infrastructure claim or assertion to verify (e.g., 'Is GLM-5.3 Flash free on ZenMux?').

Output Schema

TableJSON Schema

Name	Required	Description
`id`	No	Unique verification record ID
`answer`	Yes	Detailed explanation backed by fresh sources
`sources`	Yes	Fresh evidence sources used for verification
`verdict`	Yes	Deterministic evidence-backed verdict
`confidence`	Yes	Confidence score between 0.0 and 1.0

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 19, 2026
- addedInput schema / properties / depth / default
```
Added value: +"standard"
```

Changed3 schema fields changedSep 19, 2026

addedInput schema / properties / depth

Added value: +{
+  "description": "Verification depth: 'standard' (0.01 USDC) or 'deep' (0.03 USDC).",
+  "enum": [
+    "standard",
+    "deep"
+  ],
+  "type": "string"
+}

addedInput schema / properties / query / description

Added value: +"The specific AI infrastructure claim or assertion to verify (e.g., 'Is GLM-5.3 Flash free on ZenMux?')."

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "answer": {
+      "description": "Detailed explanation backed by fresh sources",
+      "type": "string"
+    },
+    "confidence": {
+      "description": "Confidence score between 0.0 and 1.0",
+      "type": "number"
+    },
+    "id": {
+      "description": "Unique verification record ID",
+      "type": "string"
+    },
+    "sources": {
+      "description": "Fresh evidence sources used for verification",
+      "items": {
+        "properties": {
+          "title": {
+            "description": "Source page title",
+            "type": "string"
+          },
+          "type": {
+            "description": "Source type (official, third_party, community)",
+            "type": "string"
+          },
+          "url": {
+            "description": "Source URL",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "verdict": {
+      "description": "Deterministic evidence-backed verdict",
+      "enum": [
+        "TRUE",
+        "FALSE",
+        "PARTIALLY_TRUE",
+        "CHANGED",
+        "UNREACHABLE",
+        "BLOCKED",
+        "UNVERIFIED"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "verdict",
+    "answer",
+    "confidence",
+    "sources"
+  ],
+  "type": "object"
+}

First observedSep 18, 2026

TDQS

A4.5/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnly/idempotent/destructive annotations, the description discloses important behavioral traits: it uses live web evidence, returns deterministic verdicts with cited sources and confidence scores, and requires an x402 micropayment. This significantly helps an agent understand side effects and expectations before calling the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured, with the core purpose and output format front-loaded, followed by cost, and then explicit usage boundaries. Every sentence adds operational value with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has an output schema and the description covers purpose, verdict categories, citation behavior, cost, and when not to use it. The x402 payment requirement is clearly stated, and the schema covers depth variants, so an agent has sufficient context to invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters and examples. The description adds the payment requirement and general purpose, but does not materially deepen parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with a specific verb ('Verify') and clearly identifies the resource: AI model, API provider, pricing claim, or infrastructure assertion. It also names the deterministic verdict set, making the tool's scope unambiguous and distinct from general web search and the sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides 'When to use' and 'When NOT to use' guidance, including exclusions for general web search, coding assistance, and non-AI claims. It does not name specific alternative tools to use in those excluded cases, so it falls just short of a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Verify-api tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?