MCP Queen

Search Trust Evidence

search_trust_evidence

Read-only

Search published MCP trust evidence and reviewed real-usage field reports. Use for questions such as which servers expose citations, have access caveats, make unverifiable corpus claims, or show security concerns. Returns verbatim observations with dates and source type, not a synthetic trust score.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Max evidence items (default 20, max 50)
`query`	Yes	Evidence, claim, source, capability, caveat, or server keyword
`status`	No
`dimension`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes
`results`	Yes
`returned`	Yes
`safety_notice`	Yes
`interpretation`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedAug 8, 2026

addedOutput schema / properties / safety_notice
```
Added value: +{
+  "type": "string"
+}
```

changedOutput schema / required

Previous value: -[
-  "query",
-  "returned",
-  "interpretation",
-  "results"
-]New value: +[
+  "safety_notice",
+  "query",
+  "returned",
+  "interpretation",
+  "results"
+]

Changed1 schema field changedJul 29, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "interpretation": {
+      "type": "string"
+    },
+    "query": {
+      "type": "string"
+    },
+    "results": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "dimension": {
+            "type": "string"
+          },
+          "evidence": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "evidence_page": {
+            "type": "string"
+          },
+          "metric": {
+            "type": "string"
+          },
+          "observed_at": {
+            "type": "string"
+          },
+          "sample_size": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "server_name": {
+            "type": "string"
+          },
+          "source_type": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "status": {
+            "type": "string"
+          },
+          "title": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "value_text": {
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "required": [
+          "server_name",
+          "dimension",
+          "metric",
+          "status",
+          "observed_at",
+          "evidence_page"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "returned": {
+      "type": "number"
+    }
+  },
+  "required": [
+    "query",
+    "returned",
+    "interpretation",
+    "results"
+  ],
+  "type": "object"
+}

AddedJul 16, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds that output is 'verbatim observations with dates and source type, not a synthetic trust score,' providing useful behavioral context beyond the annotations.

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 two sentences, front-loaded with purpose and followed by output scope. Every sentence adds value with no redundant phrasing.

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

Completeness4/5

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

Given the output schema exists and annotations cover safety, the description adequately covers purpose, scope, and output nature. It does not detail all query/filter behaviors, but the tool is a search interface with clear intent and output characteristics.

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 descriptions cover query and limit, but status and dimension have no descriptions. The description's example questions add context for query, but does not explain enum semantics for the other two parameters. With 50% schema coverage, some compensation exists but it is incomplete.

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 uses a specific verb ('Search') and resource ('published MCP trust evidence and reviewed real-usage field reports'). It distinguishes from siblings by clarifying that it returns evidence, not grades or synthetic scores, and provides concrete example questions it can answer.

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 implies usage for evidence-gathering questions and explicitly contrasts with synthetic trust scores, guiding when to use it for verbatim observations. It does not name alternatives or state when not to use, but the context is clear.

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

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