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ragflow-kb-mcp

ragflow-kb-mcp

by feci
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

ragflow_list_memories

Read-only

List agent conversation memory stores with their types and models, and filter by tenant, memory type, storage format, or keywords using pagination.

Instructions

List memories (agent conversation memory stores) with their types and models.

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_list_memories"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoPage number, starting at 1
keywordsNoFuzzy match on memory names
page_sizeNoItems per page
tenant_idsNoOnly memories owned by these tenants
memory_typesNoOnly memories that include one of these types
storage_typeNoStorage format filter, e.g. table

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 covered. The description adds the domain framing of what a memory is but says nothing about pagination behavior, default result size, or ordering despite paging parameters existing.

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 well-formed sentence with the verb and resource front-loaded and zero padding. Its only weakness is that brevity comes at the cost of usage and filtering context.

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?

An output schema exists and all six parameters are documented, so the mechanical requirements are met. However, for a list tool with multiple filter dimensions (tenant, memory type, storage type), an agent gets no guidance on filter semantics or result ordering from the description.

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% — page, keywords, page_size, tenant_ids, memory_types, and storage_type are all documented in the schema. The description adds no parameter meaning beyond that, so 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?

Specific verb 'List' plus resource 'memories', with a parenthetical defining memories as agent conversation memory stores. That clarification distinguishes it from sibling tools like ragflow_list_memory_messages or ragflow_get_memory_config, though it doesn't explicitly name those alternatives.

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?

No statement of when to use this versus the sibling memory tools (list_memory_messages, search_memory_messages, recent_memory_messages, get_memory_config). The agent must infer selection criteria from names alone.

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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