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Remember

remember
Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already provide idempotentHint: true. The description adds useful context: key-value scoped by identifier, persistence (24h for anonymous), and that it's a write operation. No contradictions.

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 (4-5 sentences), front-loaded with purpose, and well-structured. Every sentence adds value without redundancy.

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

Completeness5/5

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

For a simple write tool with 2 parameters and no output schema, the description is complete. It explains persistence, scope, and related tools, leaving no gaps.

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 key and value. The description adds examples but does not significantly enhance understanding beyond the schema, earning a baseline 3.

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 verb 'save' and the resource 'data to reuse later', distinguishing it from sibling tools like recall and forget. It specifies the action and scope.

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

Usage Guidelines5/5

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

Explicitly provides when to use: 'when you discover something worth carrying forward' with concrete examples. It also pairs with recall and forget, guiding proper usage.

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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TDQS

A3.6/5.0
Disambiguation2/5

Many tools overlap in purpose, such as the multiple Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) and the several query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research). Memory tools (remember, recall, forget) also add to the confusion.

Naming Consistency3/5

Tool names are mostly snake_case but vary in pattern: some are verb_noun (add_duration, compare_entities), others are noun_noun (entity_profile, date_diff) or single verbs (forget). This mix reduces predictability but is not chaotic.

Tool Count2/5

The server name 'Datecalc' implies a narrow focus, yet 33 tools exist covering far more than date calculations. The count is too high for the implied purpose, and many tools are unrelated to the server's apparent domain.

Completeness2/5

For the implied date calculation domain, only three tools exist (add_duration, date_diff, date_info), leaving obvious gaps. For the actual broad data access domain, coverage is better but still lacks a cohesive structure.