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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_update_dataset

Update RAGFlow dataset settings like name, language, parser, or embedding model; only the fields you pass change, leaving other settings intact.

Instructions

Update dataset settings. Only the fields you pass change.

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_update_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNo
languageNo
pagerankNo
parser_idNoDefault chunking method for newly parsed documents
dataset_idYesDataset (knowledge base) ID
permissionNo
descriptionNo
embedding_modelNoOnly allowed while the dataset has no chunks

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare a non-read-only, non-destructive, closed-world mutation. The description adds meaningful context beyond that: it is a partial/patch-style update where untouched settings are preserved. It says nothing about permission requirements or side effects such as re-parsing or model constraints, so the added value is real but thin.

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?

Two short sentences, front-loaded with the action and followed by the one non-obvious semantic. Nothing is wasted.

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?

With an output schema and safety annotations present, the description's remaining burden is the mutation semantics, which it partly covers. For an 8-parameter mutation with 38% schema coverage, it undersells constraints like the embedding_model limitation (documented only in schema) and permission implications.

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 coverage is only 38% across 8 parameters, so the description should compensate more. 'Only the fields you pass change' clarifies that omitted fields remain unchanged, but it does not resolve whether explicitly passing null clears a value or is a no-op, and it does not describe the permission or pagerank fields.

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?

States a specific verb and resource ('update dataset settings'), so an agent can tell it is a dataset mutation rather than a document, chat, or agent update. It does not name a sibling or differentiate itself from the other update_* tools beyond the resource noun.

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 versus alternatives, no prerequisites, and no exclusions. The partial-update sentence hints at usage but is about mechanics, not about choosing this tool.

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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