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MCP Knowledge Base Server

MCP Knowledge Base Server

by Sachin-wish
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_document

Retrieve the complete Markdown text of a knowledge-base article using its document ID, enabling direct access to full content for grounded answers.

Instructions

Fetch the full Markdown content of one knowledge-base article.

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": {
      "doc_id": "<doc_id>"
    },
    "name": "get_document"
  }
}

Input Schema

NameRequiredDescriptionDefault
doc_idYesThe id returned by search_knowledge_base or list_documents, e.g. "engineering/deploy-guide".

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does a reasonable job: 'Fetch' indicates a read-only operation, and 'full Markdown content' specifies the response format. It does not mention error/failure behavior or whether auth is required, but for a simple one-id getter this is adequate.

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?

A single, front-loaded sentence that says exactly what the tool does with no filler. It earns its place and leaves nothing to parse.

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?

For a one-parameter fetch tool with a rich parameter description and an output schema, the description is complete enough: it identifies the resource, output format, and article scope. Explicit sibling routing would help but is not necessary for correct invocation.

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% and the doc_id parameter is well documented with its source and an example. The tool description itself adds no parameter-level information, so the baseline of 3 applies.

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 states a specific action ('Fetch') and resource ('knowledge-base article'), and 'full Markdown content' clearly distinguishes it from sibling tools like search_knowledge_base or list_documents. An agent can infer the exact function without opening the schema.

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

Usage Guidelines3/5

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

Usage is implied rather than explicit: fetch full content when you need an article's Markdown, and the doc_id parameter description says the id comes from search_knowledge_base or list_documents. However, the description itself does not state when to prefer this over alternatives or what prerequisites exist.

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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