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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_upload_file

Upload files into the RAGFlow file manager for later dataset linking, not directly into datasets; provide text, base64 content, or a server file path to store them.

Instructions

Upload a file into the file manager (not into a dataset); link it to datasets later if needed.

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_upload_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
textNoUTF-8 text content
filenameNoFile name; required for text and content_base64
file_pathNoPath on the MCP server host, inside an allowed upload root
parent_idNoFolder ID; omit for the root folder of the file manager
content_base64NoFile bytes as base64 (small files only)

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds the useful lifecycle fact that uploaded files are not bound to a dataset and can be linked later, but says nothing about overwrite behavior, size/root restrictions for file_path, or error modes for a write operation.

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 zero filler; the scoping caveat is placed first where it matters. It is slightly too terse for a five-parameter write tool, leaving room for one more clause on input sources.

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 complete schema, an output schema (so return values need no explanation), and annotations covering the safety profile, the description supplies what selection needs: which storage area the file lands in and how it relates to datasets later. Minor gap is guidance on choosing among the four alternative content sources, though the schema carries that.

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%, so all five parameters (text, filename, file_path, parent_id, content_base64) are already documented, including the upload-root constraint and folder semantics. The description adds no further meaning 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (upload a file) and scopes it precisely to the file manager, explicitly contrasting with the dataset path ('not into a dataset'). This lets an agent distinguish it from ragflow_upload_document and ragflow_upload_agent_file without inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context: use this when the file belongs in the file manager rather than a dataset, and it points toward the follow-up workflow ('link it to datasets later if needed'), which maps to ragflow_link_files_to_datasets. It stops short of naming alternatives explicitly or stating when dataset upload is preferable.

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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