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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_get_dataset

Read-only

Retrieve a single RAGFlow knowledge base dataset and its parser configuration using the dataset ID.

Instructions

Get one dataset, including its parser configuration.

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": {
      "dataset_id": "<dataset_id>"
    },
    "name": "ragflow_get_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
dataset_idYesDataset (knowledge base) ID

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 fully covered without the description. The description adds only the useful detail that parser configuration is returned; it says nothing about error behavior for missing IDs or response shape.

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?

A single front-loaded sentence with no filler; the included-content detail ('parser configuration') is placed immediately after the core action. It is perhaps terse relative to what it could convey, but nothing is wasted.

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 one-parameter read-only tool with an output schema and full annotation coverage, the description supplies the essential action and returned scope. The lack of usage routing or failure-mode notes is a minor gap given the rich structured fields.

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 single parameter is documented as 'Dataset (knowledge base) ID', so the schema carries the burden. The description adds no format, naming, or lookup semantics beyond what the schema provides, warranting the baseline 3.

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 ('Get') and resource ('one dataset') and adds that the parser configuration is included, which distinguishes it from list/create/update dataset siblings. It does not explicitly name an alternative, but the singular scope is unambiguous.

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 explicit when-to-use guidance, no preconditions, and no mention of alternatives like ragflow_list_datasets or ragflow_update_dataset. The only hint is the singular 'one dataset', which implies fetching a known dataset by ID rather than enumerating.

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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