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Corpus-KB

Corpus-KB

by moliver28
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Hybrid search across code, markdown, or text chunks using vector and full-text retrieval. Filter results by source type.

Instructions

Hybrid search (vector + full-text + RRF) across all chunks.

Args: query: Natural language query. k: Number of results (max 50). source_type: Optional filter: "code", "markdown", or "text".

Returns: List of search results with text, source, score, and metadata.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search"
  }
}

Input Schema

NameRequiredDescriptionDefault
kNo
queryYes
source_typeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

The description explains the hybrid search (vector + full-text + RRF) and scope (across all chunks). With no annotations, it covers the main behavioral traits but omits details like read-only nature or performance implications.

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 concise and front-loaded with the main purpose. The args and returns are listed in a clear, no-waste format. Every sentence adds value.

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 parameter count and presence of an output schema, the description covers purpose, parameters, and return structure. It could be more explicit about the scope (e.g., 'all chunks in the database') but is otherwise sufficient.

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

Parameters5/5

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

Schema property descriptions are absent (coverage 0%), but the description provides clear explanations for each parameter: query as natural language, k as max 50, source_type with allowed values. This fully compensates for the missing schema descriptions.

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

Purpose4/5

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

The description clearly states the tool performs hybrid search across all chunks, specifying the verb and resource. However, it does not explicitly differentiate from sibling search tools like search_context or search_similar.

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?

No guidance is provided on when to use this tool versus alternatives. The description lists parameters but does not give context or exclusions.

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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