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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_list_chats

Read-only

Lists chat assistants with linked datasets and retrieval settings, enabling you to review RAGFlow assistant configurations and select the right one.

Instructions

List chat assistants with their datasets and retrieval settings.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ragflow_list_chats"
  }
}

Input Schema

NameRequiredDescriptionDefault
descNo
nameNoExact chat assistant name
pageNoPage number, starting at 1
chat_idNoReturn only this chat assistant
orderbyNocreate_time
keywordsNoMatch chat assistant names
page_sizeNoItems per page

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is clear. The description adds that returned items include datasets and retrieval settings, but it does not mention pagination, sorting, or other operational behavior despite the tool having page and page_size parameters.

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 a single front-loaded sentence with no wasted words. It is efficient, though it may be too sparse for a seven-parameter list tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has a rich schema, an output schema, and read-only annotations, which reduce the description's burden. However, for a list operation with paging, filtering, and sorting parameters, the description does not explain when to use filters or how results are ordered, leaving a clear contextual gap.

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 71%, so most documented parameters already have meaning in the schema. The description adds no parameter-level detail beyond the general purpose, leaving several parameters (such as desc and orderby) without descriptive context.

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 uses a clear verb-resource pair ('List chat assistants') and adds that results include datasets and retrieval settings. It is distinguishable from sibling retrieval tools like ragflow_get_chat, though it does not name alternatives explicitly.

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?

There is no guidance on when to use this list tool versus ragflow_chat, ragflow_get_chat, or ragflow_list_chat_sessions. Usage is only implied by the verb 'List', with no exclusions or alternative-routing instructions.

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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