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liiklin

Dify Knowledge MCP Server

by liiklin

query_dify_knowledge

Search and retrieve information from a Dify knowledge base using natural language queries to find relevant answers and data.

Instructions

Query Dify knowledge base with a search query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query to find relevant knowledge
top_kNoNumber of results to return (default: 3)
search_methodNoSearch method to usehybrid_search
reranking_enableNoEnable reranking of search results
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but only states the basic action without revealing important traits. It doesn't mention whether this is a read-only operation, what permissions are needed, rate limits, error conditions, or what format results are returned in. For a search tool with no annotation coverage, this leaves significant behavioral gaps.

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 a single, efficient sentence that states the core purpose without any wasted words. It's appropriately sized for a search tool and front-loads the essential information. Every word earns its place in communicating the tool's function.

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 tool has 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what kind of results to expect, how they're structured, or important behavioral aspects like authentication requirements or error handling. For a knowledge base query tool with multiple configuration parameters, more context is needed to guide effective use.

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 description mentions 'with a search query' which aligns with the 'query' parameter, but adds no additional semantic context beyond what the schema already provides. With 100% schema description coverage and detailed parameter documentation including defaults and enums, the description doesn't compensate with extra meaning. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 verb ('Query') and resource ('Dify knowledge base') with the action ('with a search query'), making the purpose immediately understandable. It distinguishes from the sibling tool 'get_dify_config' by focusing on search operations rather than configuration retrieval. However, it doesn't specify what kind of knowledge base content is being queried (documents, FAQs, etc.), keeping it from a perfect score.

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 or in what context. There's no mention of prerequisites, limitations, or comparison with the sibling tool 'get_dify_config'. The agent must infer usage purely from the tool name and parameters without any explicit direction.

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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