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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_create_memory

Create a memory to store agent conversations and extract raw dialogue, semantic facts, episodic events, or procedural habits for later retrieval.

Instructions

Create a memory that stores and extracts agent conversations.

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": {
      "name": "<name>",
      "llm_id": "<llm_id>"
    },
    "name": "ragflow_create_memory"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesMemory name (max 128 characters)
llm_idYesChat model that extracts memories, as model_name@factory
descriptionNoShort description
memory_typesNoWhat to keep: raw dialogue, semantic facts, episodic events, procedural habits
embedding_modelNoEmbedding model as model_name@factory; defaults to the server's configured default

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 this is a non-read-only, non-destructive, closed-world operation, so the safety profile is covered. The description adds useful behavioral context that the memory stores and extracts conversations, but does not disclose persistence implications, LLM dependency, or extraction behavior in detail.

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?

A single, front-loaded sentence with no filler. It communicates the core action immediately.

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 schema, annotations, and output schema are rich, so much of the burden is already covered. However, for a creation tool with multiple behavioral parameters, the description is minimal and leaves usage context and extraction semantics 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%, so all parameters including name, llm_id, description, memory_types, and embedding_model are already documented in the schema. The description adds no parameter-level detail, so the baseline of 3 is appropriate.

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: creating a memory, and clarifies that this memory stores and extracts agent conversations. It distinguishes creation from sibling memory tools like list/update/delete, though it does not explicitly contrast with them.

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?

Provides no explicit guidance on when to use this tool versus ragflow_list_memories, ragflow_update_memory, or ragflow_add_memory_message. The use case is only implied by the purpose statement.

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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