Vascue Public Knowledge Search

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Read-onlyIdempotent

Hybrid keyword + semantic search over the public pages of vascue.io: healthcare-operations guides, the AI front desk for clinics, provider-side insurance-claims automation, Cliniko and Nookal integration, security and compliance pages, case studies, pricing and blog posts.

Use it to answer questions about what Vascue offers, how its products work and what it has published. One topic per call; cite the returned page URL for every excerpt you use.

Returns a JSON text payload: result.chunks[] ordered by relevance, each with text (a Markdown excerpt), score (0-1, higher is better) and item.metadata.url (the canonical https://www.vascue.io/... page). Off-topic queries still return the nearest chunks, so treat scores below about 0.5 as weak evidence and say so when the site does not cover a topic.

Read-only and idempotent; no authentication; 60 requests per minute per client. Public content only: never send patient information, claim documents, clinic credentials or booking requests. It cannot book appointments or look up clinic data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	What to look for, as a natural-language question or keywords, e.g. "how does claims pre-authorisation work" or "Cliniko integration". 3-15 words works best; one topic per call.
`ai_search_options`	No	Optional retrieval tuning. Omit for the defaults: hybrid search, 8 results, score threshold 0.35.

Schema Changelog

Changes observed during successful MCP inspections.

Changed15 schema fields changedAug 23, 2026

removedInput schema / $schema

Removed value: -"http://json-schema.org/draft-07/schema#"

changedInput schema / properties / ai_search_options / description

Previous value: -"Options for customizing the AI search behavior."New value: +"Optional retrieval tuning. Omit for the defaults: hybrid search, 8 results, score threshold 0.35."

removedInput schema / properties / ai_search_options / properties / cache

Removed value: -{
-  "properties": {
-    "cache_threshold": {
-      "type": "string"
-    },
-    "enabled": {
-      "type": "boolean"
-    }
-  },
-  "type": "object"
-}

removedInput schema / properties / ai_search_options / properties / query_rewrite

Removed value: -{
-  "properties": {
-    "enabled": {
-      "const": false,
-      "type": "boolean"
-    },
-    "rewrite_prompt": {
-      "type": "string"
-    }
-  },
-  "type": "object"
-}

removedInput schema / properties / ai_search_options / properties / reranking

Removed value: -{
-  "properties": {
-    "enabled": {
-      "const": false,
-      "type": "boolean"
-    },
-    "match_threshold": {
-      "maximum": 1,
-      "minimum": 0,
-      "type": "number"
-    }
-  },
-  "type": "object"
-}

addedInput schema / properties / ai_search_options / properties / retrieval / properties / context_expansion / description
```
Added value: +"Neighbouring chunks from the same page to include around each hit (default 0)."
```

removedInput schema / properties / ai_search_options / properties / retrieval / properties / filters

Removed value: -{
-  "additionalProperties": {
-    "anyOf": [
-      {
-        "anyOf": [
-          {
-            "type": "string"
-          },
-          {
-            "type": "number"
-          },
-          {
-            "type": "boolean"
-          },
-          {
-            "type": "null"
-          }
-        ]
-      },
-      {
-        "properties": {
-          "$eq": {
-            "anyOf": [
-              {
-                "type": "string"
-              },
-              {
-                "type": "number"
-              },
-              {
-                "type": "boolean"
-              },
-              {
-                "type": "null"
-              }
-            ]
-          },
-          "$gt": {
-            "anyOf": [
-              {
-                "type": "string"
-              },
-              {
-                "type": "number"
-              }
-            ]
-          },
-          "$gte": {
-            "anyOf": [
-              {
-                "type": "string"
-              },
-              {
-                "type": "number"
-              }
-            ]
-          },
-          "$in": {
-            "items": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "number"
-                },
-                {
-                  "type": "boolean"
-                },
-                {
-                  "type": "null"
-                }
-              ]
-            },
-            "type": "array"
-          },
-          "$lt": {
-            "anyOf": [
-              {
-                "type": "string"
-              },
-              {
-                "type": "number"
-              }
-            ]
-          },
-          "$lte": {
-            "anyOf": [
-              {
-                "type": "string"
-              },
-              {
-                "type": "number"
-              }
-            ]
-          },
-          "$ne": {
-            "anyOf": [
-              {
-                "type": "string"
-              },
-              {
-                "type": "number"
-              },
-              {
-                "type": "boolean"
-              },
-              {
-                "type": "null"
-              }
-            ]
-          },
-          "$nin": {
-            "items": {
-              "anyOf": [
-                {
-                  "type": "string"
-                },
-                {
-                  "type": "number"
-                },
-                {
-                  "type": "boolean"
-                },
-                {
-                  "type": "null"
-                }
-              ]
-            },
-            "type": "array"
-          }
-        },
-        "type": "object"
-      }
-    ]
-  },
-  "propertyNames": {
-    "type": "string"
-  },
-  "type": "object"
-}

removedInput schema / properties / ai_search_options / properties / retrieval / properties / fusion_method
```
Removed value: -{
-  "enum": [
-    "max",
-    "rrf"
-  ],
-  "type": "string"
-}
```

addedInput schema / properties / ai_search_options / properties / retrieval / properties / match_threshold / description

Added value: +"Minimum relevance score for a chunk to be included (default 0.35); raise for precision, lower for recall."

addedInput schema / properties / ai_search_options / properties / retrieval / properties / max_num_results / description
```
Added value: +"Maximum chunks to return (default 8)."
```
removedInput schema / properties / ai_search_options / properties / retrieval / properties / metadata_only
```
Removed value: -{
-  "type": "boolean"
-}
```

addedInput schema / properties / ai_search_options / properties / retrieval / properties / retrieval_type / description

Added value: +"hybrid (default) fuses keyword and vector ranking; keyword for exact phrases or product names; vector for paraphrased questions."

changedInput schema / properties / ai_search_options / properties / retrieval / properties / retrieval_type / enum

Previous value: -[
-  "vector",
-  "keyword",
-  "hybrid"
-]New value: +[
+  "hybrid",
+  "vector",
+  "keyword"
+]

removedInput schema / properties / ai_search_options / properties / retrieval / properties / return_on_failure
```
Removed value: -{
-  "type": "boolean"
-}
```

changedInput schema / properties / query / description

Previous value: -"The input query."New value: +"What to look for, as a natural-language question or keywords, e.g. \"how does claims pre-authorisation work\" or \"Cliniko integration\". 3-15 words works best; one topic per call."

First observedAug 21, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The description goes well beyond the annotations by disclosing rate limits (60 requests per minute per client), no authentication, read-only and idempotent behavior, and content restrictions. It also warns that off-topic queries still return nearest chunks and that low scores are weak evidence. This is strong behavioral context that helps the agent set expectations and respond honestly.

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 dense but well organized: capabilities first, usage rules next, response shape, then safety boundaries. Every sentence adds information needed for correct invocation or interpretation, with no filler or tautology.

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?

Despite having no output schema, the description fully compensates by detailing the response shape (result.chunks[] with text, score, item.metadata.url) and expected behavior on low scores. With rich parameter schema plus this description, the agent has everything needed to invoke the tool and interpret results 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 the query and ai_search_options parameters thoroughly, including retrieval types, thresholds, and defaults. The description adds usage nuance such as 'one topic per call' and the 0.5 score interpretation, but those overlap with schema guidance and do not substantially improve parameter understanding beyond it.

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 clearly identifies the tool as hybrid keyword + semantic search over Vascue's public documentation, enumerating the exact content areas (healthcare-operations guides, integrations, security pages, blog posts, etc.). It also gives the intended use — answering questions about Vascue's products and published content — which fully distinguishes the tool's purpose even without siblings.

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

Usage Guidelines5/5

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

It explicitly states when to use the tool: to answer questions about what Vascue offers and how products work. It also spells out usage constraints: one topic per call, cite returned page URLs for every excerpt, treat scores below about 0.5 as weak evidence, and avoid sending patient information or clinic credentials. The closing boundary — cannot book appointments or look up clinic data — prevents misuse.

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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