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universal-memory-mcp

store_memory

Save a new memory with content, type (episodic, semantic, procedural), and optional agent/session scoping, importance rating, metadata, and graph links to related memories.

Instructions

Store a new memory with optional agent/session scoping, semantic embedding, and graph links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linksNoGraph links to create from this new memory to existing memories.
contentYesMemory content text to store
agent_idNoAgent identifier (e.g. 'principal_investigator'). None = shared memory.
metadataNoJSON string of additional metadata (task_id, experiment_id, etc.)
importanceNoSalience score 0.0-1.0 for pruning priority. Default 0.5.
session_idNoSession identifier for grouping memories. None = unscoped.
memory_typeYesType: 'episodic' (events/logs), 'semantic' (facts/knowledge), 'procedural' (how-to/workflows)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions optional scoping, embedding, and links, but does not disclose operational traits such as idempotency, permissions required, side effects of invalid inputs (e.g., non-existent link targets), or any constraints on memory creation. For a tool with 7 parameters, this is insufficient.

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 a single concise sentence of 14 words, stating the core action and key optional features. It is front-loaded with the verb and resource, containing no filler or redundant information.

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?

Given the tool has 7 parameters, 2 required, an output schema, and no annotations, the description covers the high-level purpose but omits details about behavior (e.g., whether it returns the created memory), error conditions, or constraints on required parameters. The output schema may fill some gaps, but for a creation tool, more context would improve agent confidence.

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 description coverage is 100%, so the baseline is 3. The description adds context by naming 'agent/session scoping' (mapping to agent_id/session_id), 'graph links' (mapping to links), and 'semantic embedding' (implied by memory_type). While helpful, it does not provide additional semantic depth beyond what the schema already documents.

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 action ('Store a new memory') and identifies the resource as a memory. It distinguishes this tool from siblings like recall_memories (retrieval), update_memory (modification), manage_session (session management), and memory_admin (admin tasks) by positioning it as the creation action.

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?

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, when not to use it, or direct users to other tools for related tasks. The sibling tool names provide implicit context, but the description itself lacks any usage direction.

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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