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Mnemo - Persistent AI Memory

by n24q02m
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

list_memories

Read-only

Browse all memories or filter by category to inspect what an AI remembers. Use it to review stored preferences and past context before responding.

Instructions

Browse all memories, optionally filtered by category.

ACTION GUIDE — when to use:

  • Use when you want to view a broad set of memories, or see what's in a specific category. Example: category='preference', limit=10

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv2.6.0
    • addedOutput schema / additionalProperties
      Added value: +true
    • removedOutput schema / properties
      Removed value: -{
-  "result": {
-    "title": "Result",
-    "type": "string"
-  }
-}
    • removedOutput schema / required
      Removed value: -[
-  "result"
-]
    • changedOutput schema / title
      Previous value: -"list_memoriesOutput"New value: +"list_memoriesDictOutput"
  2. Addedv2.1.1

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds filter behavior but does not disclose pagination, ordering, or other operational details.

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?

The description is concise, with the purpose in the first sentence and an example. Every sentence adds value, no redundancy.

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 an output schema present and good annotations, the description covers key aspects. Missing ordering or default behavior, but adequate for a simple list tool.

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 0%, so the description must compensate. It explains 'category' and 'limit' through example but does not detail valid values or constraints.

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?

The description clearly states the tool browses memories with optional category filtering. It implies a broad listing, distinguishing it from siblings like search_memory, but does not explicitly name alternatives.

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?

The ACTION GUIDE explicitly advises when to use: for broad views or category-specific listings, with an example. It lacks exclusionary guidance (when not to use) but provides clear context.

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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