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Glama

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only and idempotent behavior. The description adds value by explaining scoping (anonymous IP, BYO key hash, account ID) which is not in annotations. 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?

Three concise sentences that front-load the main purpose, with no wasted words. Every sentence adds value.

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 tool with one optional parameter and no output schema, the description fully covers usage, scoping, and relationships with siblings. 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 has 100% coverage with a clear description for the 'key' parameter. The description reinforces that omitting the key lists all keys, but adds little beyond the schema.

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 the verb (retrieve/list) and resource (saved memories). It distinguishes from siblings like 'remember' and 'forget' by explicitly mentioning them and contrasting the action.

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?

Describes when to use (looking up previously stored context) and provides context about scoping to an identifier. Does not explicitly state when not to use, but the pairing with 'remember' and 'forget' implies alternatives.

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

A4.1/5.0
Disambiguation5/5

Each tool has a detailed description clarifying its precise purpose, and even closely related tools (e.g., ask_pipeworx vs ask_pipeworx_grounded) are clearly differentiated by behavior and use case. No two tools appear to serve the same function.

Naming Consistency3/5

All names use snake_case, but the structural pattern is inconsistent: many follow verb_noun (compare_entities, resolve_entity), while others are noun-based (entity_profile, polymarket_arbitrage) or single verbs (subscribe, remember). This mix reduces predictability.

Tool Count3/5

With 32 tools, the server is quite large for an MCP server. While many tools are justified by the broad domain coverage, the high number can overwhelm agents and increase cognitive load, making it feel somewhat bloated.

Completeness4/5

The tool set covers a wide range of domains (company data, prediction markets, news, memory, subscriptions, etc.), and the generic ask_pipeworx and deep_research tools gateways to thousands of data sources, effectively filling gaps. However, some areas lack dedicated tools (e.g., weather, real estate) beyond the generic query.