Smara Memory MCP Server

Store Memory

store_memory

Store user facts and preferences with automatic deduplication and contradiction detection. Assign importance scores to control memory decay rates for trivia, general facts, or critical information.

Instructions

Store a fact or preference about a user. Smara handles deduplication and contradiction detection automatically. Use importance 0.1-0.3 for trivia, 0.5 for general facts, 0.7-1.0 for critical preferences.

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": {
      "user_id": "<user_id>",
      "fact": "<fact>"
    },
    "name": "store_memory"
  }
}

Input Schema

Name	Required	Description
`user_id`	Yes	Unique identifier for the user
`fact`	Yes	The fact or preference to remember
`importance`	No	Importance score (0-1). Higher = slower decay.
`namespace`	No	Memory namespace for isolation (default: from env or 'default')
`visibility`	No	Who can see this memory. Use 'team' for project decisions, architecture, conventions, shared knowledge — anything a teammate needs. Use 'private' for personal preferences, editor settings, individual style choices. Only applies when SMARA_TEAM_ID is set.
`team_id`	No	Team ID to store this memory under. Defaults to SMARA_TEAM_ID env var if set.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.2.0Apr 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool stores data, handles deduplication and contradiction detection automatically, and explains the impact of importance scores on decay rates. It does not cover aspects like error conditions, performance, or rate limits, but provides substantial context for a mutation 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 appropriately sized and front-loaded, with two sentences that efficiently convey core functionality and usage guidance. Every sentence adds value without redundancy, making it easy to parse and understand quickly.

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 the tool's complexity as a mutation tool with 6 parameters and no annotations or output schema, the description is largely complete. It covers purpose, behavioral traits, and usage guidelines, but could benefit from mentioning potential side effects, error handling, or return values to fully compensate for the lack of structured data.

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?

The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds some semantic context by explaining the importance parameter's practical usage (e.g., trivia vs. critical preferences), but does not provide additional meaning for other parameters beyond what the schema offers, aligning with the baseline for high schema coverage.

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's purpose with a specific verb ('Store') and resource ('a fact or preference about a user'), distinguishing it from siblings like delete_memory, update_memory, list_memories, and search_memories. It also mentions the system's automatic handling of deduplication and contradiction detection, which adds unique functional context.

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 provides explicit guidance on when to use the tool by detailing importance score ranges (e.g., 0.1-0.3 for trivia, 0.5 for general facts, 0.7-1.0 for critical preferences), which helps in decision-making. However, it does not explicitly mention when not to use it or name alternatives among siblings, such as update_memory for modifications.

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

Deploy Server