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vector-mcp

vector-mcp

by Knuckles-Team
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Search

vector_search
Read-onlyIdempotent

Perform hybrid vector searches across multiple databases using semantic and lexical weights to retrieve relevant results for RAG and AI agents.

Instructions

Search (vector_search). Manage search operations.

Input Schema

NameRequiredDescriptionDefault
rrf_kNorrf k
db_typeNodb type
questionNoquestion
lexical_weightNolexical weight
number_resultsNonumber results
collection_nameNocollection name
semantic_weightNosemantic weight

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed10 schema fields changedv3.3.0
    • removedInput schema / properties / action
      Removed value: -{
-  "description": "Action to perform. Must be one of: 'semantic_search', 'lexical_search', 'search'",
-  "type": "string"
-}
    • removedInput schema / properties / bm25_weight
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "number"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "bm25 weight"
-}
    • removedInput schema / properties / db_name
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "db name"
-}
    • removedInput schema / properties / db_path
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "db path"
-}
    • removedInput schema / properties / host
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "host"
-}
    • addedInput schema / properties / lexical_weight
      Added value: +{
+  "anyOf": [
+    {
+      "type": "number"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "lexical weight"
+}
    • removedInput schema / properties / password
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "password"
-}
    • removedInput schema / properties / port
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "port"
-}
    • removedInput schema / properties / username
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "username"
-}
    • removedInput schema / required
      Removed value: -[
-  "action"
-]
  2. First observedv1.39.0

TDQS

C2.2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered elsewhere. The description adds no behavioral context such as how hybrid ranking works, what the weights control, or what the output contains.

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

Conciseness2/5

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

The description is short, but both sentences are essentially filler: the first repeats the name/title, and the second says only 'Manage search operations.' This is under-specification rather than useful conciseness.

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

Completeness2/5

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

With seven optional parameters, an output schema, and sibling search tools, the definition should clarify hybrid search behavior and selection criteria. The description instead provides almost no context for using the 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 by the stated baseline the schema is treated as documenting the parameters even though descriptions like 'rrf k' and 'semantic weight' are minimal. The description itself adds no parameter meaning beyond the schema.

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

Purpose2/5

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

The description says only 'Search (vector_search). Manage search operations.' This restates the tool name and title without specifying what kind of search it performs or how it differs from the sibling tools vector_semantic_search and vector_lexical_search.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus vector_semantic_search, vector_lexical_search, or any of the collection tools. The agent is left to infer context entirely from the name and schema.

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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