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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. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "key": "user_research_topic"
      +  },
      +  {}
      +]
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds context about scoping to identifier and pairing with other tools, enhancing transparency 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?

The description is two sentences long, covering purpose, usage, and scoping without redundancy. Slightly verbose but each clause adds necessary information.

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?

The tool has one optional parameter and no output schema; the description explains its behavior, usage context, and scoping. It lacks detail on return format but is sufficient for the tool's simplicity.

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% and the description merely restates that omitting the key lists all keys, which adds minimal value. The schema already clearly defines the parameter.

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 retrieves a value saved via 'remember' or lists all keys if omitted. It distinguishes itself from sibling tools 'remember' and 'forget', making the purpose unambiguous.

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 concrete examples of when to use (user's target ticker, address, research notes) and explains scoping. While it doesn't explicitly exclude other tools, the pairing with 'remember' and 'forget' makes usage clear.

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

B3.3/5.0
Disambiguation1/5

The tool set covers many unrelated domains (elevation, finance, prediction markets, AI visibility, etc.) with multiple overlapping tools per domain (e.g., three 'ask_pipeworx' variants, several 'polymarket' tools). An agent would struggle to distinguish which tool to use for a given task.

Naming Consistency2/5

Names follow no consistent pattern: some use snake_case with vague verbs (e.g., 'process', 'run'), others use descriptive but unrelated prefixes ('ai_', 'ask_pipeworx_', 'polymarket_'). There is no uniform verb_noun structure.

Tool Count3/5

With 32 tools, the count is reasonable for a large server, but the vast majority are irrelevant to the server's stated purpose (elevation). This mismatch makes the count inappropriate.

Completeness1/5

The server name 'Open Elevation' implies a focus on elevation data, yet only 2 of 32 tools (get_elevation, get_elevations) are related. There are severe gaps: no area elevation, no geocoding, no terrain analysis. The tool surface is largely off-topic.