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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_download_file

Read-only

Retrieve a file from the RAGFlow file manager as text, or return binary content as base64 when requested.

Instructions

Read a file from the file manager. Text comes back as text; binary only on request, as base64.

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": {
      "file_id": "<file_id>"
    },
    "name": "ragflow_download_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_idYesFile or folder ID in the RAGFlow file manager
max_charsNoReturn at most this many characters of text
include_base64NoReturn binary content as base64 (up to 5 MB)

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the text-vs-base64 return behavior, but this largely restates the include_base64 schema field and the output schema; it says nothing about truncation behavior, size limits, or errors on missing/inaccessible files.

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 with zero filler, and the core action is front-loaded before the output-format caveat. Nothing is redundant or padded.

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?

With a full output schema, complete parameter documentation, and safe-read annotations, the description carries little remaining burden. The main gap is that the scope boundary versus the sibling download tools (documents, agent attachments, commit files) is left implicit.

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 every parameter (file_id, max_chars, include_base64) is documented with defaults and bounds in the schema itself. The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 ('Read a file from the file manager'), which separates it from dataset-document and attachment readers in principle. It does not explicitly name or contrast with the nearby siblings ragflow_download_document, ragflow_download_agent_attachment, or ragflow_get_commit_file_content, so an agent must infer the distinction from the word 'file manager'.

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 clause 'binary only on request' implies when to set include_base64, which is useful conditional guidance. However, there is no explicit when-to-use/when-not-to-use statement and no pointer to an alternative tool for fetching documents or attachments.

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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