Skip to main content
Glama
Sign In
kb-mcp-server

kb-mcp-server

by code-runner-xx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_document_content

Retrieve and concatenate the full text of a document by its unique ID. Use this tool when you need the complete content of a document or additional context after a search.

Instructions

按 document_id 拉取并拼接单篇文档全文。

何时使用:用户要看某文档完整内容,或 search 命中后需要更完整上下文时。
参数 document_id 必须是合法 UUID(可从 list_documents 或 search_knowledge_base
的返回中获取)。超 8000 字符会自动截断并在末尾标注原始字符数。

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": {
      "document_id": "<document_id>"
    },
    "name": "get_document_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
document_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses automatic truncation at 8000 characters with original character count noted, which is a key behavioral trait. However, it doesn't mention idempotency or read-only nature, but for a fetch operation this is sufficient.

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 with four sentences, front-loaded with the main purpose. Every sentence adds value without waste.

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?

Given the simple nature (one required param, output schema exists), the description is complete. It covers truncation behavior and parameter source, which is sufficient for the AI agent to correctly invoke the tool.

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 description coverage is 0%, so the description must add meaning. It clarifies that document_id must be a valid UUID and provides sources (list_documents or search_knowledge_base), which is a significant addition beyond the schema's type definition.

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 states it fetches the full content of a single document by document_id, distinguishing it from sibling tools like list_documents (lists metadata) and search_knowledge_base (searches). The verb '拉取并拼接' (fetch and concatenate) specifies the action and resource.

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?

The description explicitly states when to use: when the user wants to see the full document content or after a search for more context. It also specifies that document_id must be a valid UUID obtainable from other tools, providing clear usage context and exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools