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Simonsms

TiDB RAG MCP Server

by Simonsms

List Knowledge Entries

tidb_list_knowledge
Read-onlyIdempotent

List knowledge entries from a RAG knowledge base, filter by category, and paginate through results to find relevant information.

Instructions

List knowledge entries from TiDB RAG knowledge base with pagination.

This tool retrieves knowledge entries from the database, supporting filtering by category and pagination.

Args:

  • limit (number): Maximum results to return, 1-100 (default: 20)

  • offset (number): Number of results to skip for pagination (default: 0)

  • category (string, optional): Filter by category

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: For JSON format: { "total": number, // Total entries matching criteria "count": number, // Entries in this response "offset": number, // Current pagination offset "items": [...], // Array of knowledge entries "has_more": boolean, // Whether more results exist "next_offset": number // Offset for next page (if has_more) }

Examples:

  • List first 10 entries: { "limit": 10 }

  • Filter by category: { "category": "技术文档", "limit": 20 }

  • Paginate: { "limit": 20, "offset": 20 }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (1-100)
offsetNoNumber of results to skip for pagination
categoryNoFilter by category
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond annotations by documenting pagination semantics, response_format options, and the JSON return contract including has_more and next_offset. It does not specify ordering or entry field shapes, but the annotation coverage lowers that burden.

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

Conciseness4/5

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

The description is well-organized with Summary, Args, Returns, and Examples sections, and the key purpose is front-loaded. There is minor redundancy: the second sentence largely restates the first ('List knowledge entries... with pagination' vs 'retrieves knowledge entries... supporting... pagination'), which costs a little efficiency.

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?

For a read-only, paginated list tool with no output schema, the description covers all parameters, defaults, pagination mechanics, JSON return shape, and includes examples. It omits markdown output shape and ordering semantics, but these are minor given the annotations and schema coverage.

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 the schema already documents all four parameters fully. The description repeats parameter defaults and adds practical examples, but it does not add substantive semantic meaning beyond what the schema provides.

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 states a specific verb and resource: 'List knowledge entries from TiDB RAG knowledge base with pagination' and adds category filtering. It is clear and distinct in practice, but it never explicitly references sibling tools like tidb_get_knowledge or tidb_search_knowledge to explain how listing differs from getting or searching.

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?

The description implies usage for paginated browsing and category filtering, which gives some context. However, it provides no explicit when-to-use or when-not-to-use guidance and does not mention alternative tools or conditions that would route an agent to search or vector_search instead.

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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