Skip to main content
Glama

memory_save

Save facts, decisions, preferences, or lessons to long-term memory. Automatically create embeddings for future semantic search.

Instructions

Save a fact, decision, preference, or lesson to long-term memory. Automatically generates an embedding for future semantic search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe memory content — be specific and self-contained
categoryNoMemory category (default: general)
projectNoAssociated project name
Behavior3/5

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

With no annotations, the description must disclose behavior. It mentions automatic embedding generation, but lacks details on side effects (e.g., overwrite behavior), auth requirements, or limits. Adequate but incomplete.

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?

Two succinct sentences: the first defines purpose, the second adds a key behavior (embedding). No superfluous words; highly efficient.

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?

Given no output schema and 3 parameters, the description covers purpose and key behavior. Missing return value info (e.g., success indicator or ID) and content length limits, but adequate for a simple save operation.

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 coverage is 100% with descriptions for all parameters. The description adds 'fact, decision, preference, or lesson' which aligns with the category enum, but does not significantly extend schema meaning beyond what is already provided.

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 the tool saves facts, decisions, preferences, or lessons to long-term memory and generates embeddings, distinguishing it from search/recent/stat siblings.

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 explicit guidance on when to use this tool vs alternatives like memory_journal or memory_search. The description implies saving personal notes but does not specify exclusions or preferred contexts.

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/DomDemetz/claude-soul'

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