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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

A4.6/5.0
Behavior4/5

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

Annotations indicate idempotentHint=true and no destructive behavior. Description adds key details like key-value scoping by identifier and specific retention policies (24h for anonymous), which go beyond annotations.

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?

Concise single paragraph front-loading the purpose. Every sentence adds value, though could be slightly tighter without losing clarity.

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?

Given the tool's simplicity (two required string params, no output schema), the description fully covers purpose, usage, behavior, and pairing with sibling tools. No gaps left for agent confusion.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers both parameters with examples. Description adds extra meaning by explaining the rationale for key naming (e.g., 'subject_property') and that value can be any text, enhancing schema descriptions.

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?

Clearly states the tool saves data for reuse across conversations/sessions, and gives concrete examples (resolved ticker, target address, etc.). Distinguishes itself from siblings recall and forget by mentioning pairing.

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 says when to use: when discovering information worth carrying forward to avoid re-lookup. Mentions pairing with recall and forget, and provides context about persistence differences between authenticated and anonymous sessions.

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

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (entity_profile, compare_entities, ask_pipeworx, etc.). However, ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are very similar, and suggest_questions/discover_tools overlap slightly. Overall, tools are well-disambiguated with only minor ambiguity.

Naming Consistency3/5

All tool names use snake_case, but the pattern is inconsistent: some start with a verb (ask_, validate_), others with a noun (entity_, bet_). Several are noun_noun (entity_profile), and some are single verbs (remember). No consistent verb_noun pattern across the set.

Tool Count2/5

33 tools is excessive for a server named 'Isbn' that only has 2 ISBN-specific tools. The majority are from Pipeworx, creating scope mismatch. Multiple redundant tools (three ask_pipeworx variants, several polymarket tools) inflate the count unnecessarily.

Completeness2/5

For a server named 'Isbn', completeness is very low—only conversion and validation are provided; no metadata lookup or other ISBN-related features exist. The Pipeworx tools themselves are comprehensive, but they do not align with the server's implied domain.