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Mnemo - Persistent AI Memory

Mnemo - Persistent AI Memory

by n24q02m
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

restore_memory

Bring an archived memory back into the active search pool by ID, making it searchable again.

Instructions

Restore an archived memory by ID.

ACTION GUIDE — when to use:

  • Use to bring a previously archived memory back into the active search pool. Example: memory_id='abc123'

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": {
      "memory_id": "<memory_id>"
    },
    "name": "restore_memory"
  }
}

Input Schema

NameRequiredDescriptionDefault
memory_idYes

Output 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: -"restore_memoryOutput"New value: +"restore_memoryDictOutput"
  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 indicate non-read-only and non-destructive. Description adds that it restores to 'active search pool' but lacks details on idempotency, error behavior, or preconditions. Adds some value beyond annotations.

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?

Short, uses bullet list for guidance. No redundant sentences. Could be slightly more front-loaded but efficient overall.

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?

Output schema exists so return values not needed. Covers basic purpose and usage. Missing details like preconditions or error cases, but for a simple restore operation it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Single parameter 'memory_id' has 0% schema coverage. Description only gives an example value but does not explain format or constraints. Minimal addition over schema.

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?

Description clearly states verb 'restore' with resource 'archived memory' and method 'by ID'. Distinguishes from sibling tools like add_memory, delete_memory, etc.

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?

Explicitly says when to use ('bring a previously archived memory back into the active search pool') and provides an example. Missing explicit when-not-to-use or alternatives, but context is clear.

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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