Skip to main content
Glama
serkansmg

smg-claude-memory-mcp

by serkansmg

memory_store

Automatically embed, summarize, extract entities, and set TTL when saving project memories for persistent context retrieval.

Instructions

Store a new memory with auto-embedding, summary, entity extraction, and TTL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
titleYes
sourceNoassistant
contentYes
projectNo
categoryYes
metadataNo
priorityNo
related_idsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, description carries full burden. It discloses auto-embedding, summary, entity extraction, TTL, but omits details like potential delays, auth needs, or side effects of TTL.

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?

Single sentence is concise and front-loaded. Could benefit from structured list of features but no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 9 parameters, no annotations, and many siblings, description is too brief. Lacks explanation of return values (output schema exists but not mentioned), parameter defaults, or workflow integration.

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 coverage is 0%, but description only vaguely mentions features not mapped to parameters. No explanation for tags, source, project, metadata, related_ids, or priority. TTL is not a parameter, causing confusion.

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 'Store a new memory' with specific verb and resource. Mentions auto-embedding, summary, entity extraction, TTL which distinguish it from siblings like memory_update, memory_search, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage for storing new memories, but no explicit when-to-use, when-not-to-use, or alternatives. Sibling tools like memory_update could be confused without guidance.

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/serkansmg/smg-claude-memory-mcp'

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