Skip to main content
Glama
n24q02m

Mnemo - Persistent AI Memory

add_memory

Store new preferences, decisions, and facts to build a persistent AI memory that retains information across sessions.

Instructions

Store NEW information. Use for preferences, decisions, facts.

ACTION GUIDE — when to use:

  • Use when saving new information for the first time. Example: content='User prefers dark mode', category='preference', tags=['ui']

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYes
categoryNo
tagsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, so the description adds little beyond stating it stores new information. No additional behavioral details such as required permissions or side effects are provided, which is acceptable for a simple creation tool.

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 a clear action guide and example. Every sentence adds value without unnecessary words.

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 description is adequate for a simple tool with 3 parameters and an output schema. It covers basic purpose and usage, but does not elaborate on return values or differentiate from many sibling tools beyond the main action.

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?

Schema description coverage is 0%, and the description does not explain individual parameters. It provides an example (content, category, tags) but lacks explicit semantics for each parameter, such as expected formats or constraints.

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?

The description clearly states 'Store NEW information' and gives specific use cases like preferences, decisions, facts. It distinguishes from sibling tools such as update_memory (which would modify existing).

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 description includes an 'ACTION GUIDE' that specifies when to use: 'when saving new information for the first time' and provides an example. However, it does not explicitly mention when not to use or name alternatives like update_memory.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/n24q02m/mnemo-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server