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KB-MCP Server

KB-MCP Server

by isshiki-dev
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JavaScript
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query_knowledge

Search a knowledge base using semantic queries to find relevant information from stored documents.

Instructions

Query the knowledge base using semantic search.

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": "query_knowledge"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesSearch query
limitNoMax results
thresholdNoMin similarity

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It states the tool performs semantic search but doesn't explain what that entails (e.g., natural language processing, vector similarity), potential limitations (e.g., accuracy, performance), or expected outcomes (e.g., relevance-ranked results). This leaves significant gaps for an agent to understand how the tool behaves.

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 extremely concise with a single sentence that directly states the tool's function. There is no wasted language or unnecessary elaboration, making it efficiently front-loaded and easy to parse.

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?

Given the complexity of a semantic search tool with 3 parameters and no annotations or output schema, the description is insufficient. It lacks details on behavior, usage context, and return values, leaving an agent with incomplete information to effectively select and invoke this tool among its siblings.

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?

The input schema has 100% description coverage, providing clear documentation for all parameters (query, limit, threshold). The description adds no additional semantic context beyond what the schema already states, such as examples of effective queries or how threshold affects results. This meets the baseline for high schema coverage.

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 action ('Query') and resource ('knowledge base') with the method ('semantic search'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_documents' or 'get_document', which might also retrieve knowledge base content but through different mechanisms.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when semantic search is appropriate compared to exact matching in 'get_document' or browsing in 'list_documents', nor does it specify prerequisites or exclusions for usage.

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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