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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

A4.7/5.0
Behavior4/5

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

Annotations already provide readOnly/idempotent/destructive hints, so the bar is lower. The description adds meaningful context beyond annotations: scoping to the identifier ('anonymous IP, BYO key hash, or account ID') and the pairing relationship with remember/forget. It does not disclose behavior for missing keys, but this is minor given the simple read operation.

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 two well-structured sentences, front-loaded with the core action. Every clause adds functional value—retrieval, listing, scope, and pairing—with no redundancy or filler.

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 simple one-parameter tool with no output schema, the description is complete: it explains how to retrieve, how to list all keys, the scope of data, and the relationship to sibling tools. No critical information is missing for correct selection and invocation.

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 coverage is 100% (the 'key' parameter is described), so baseline is 3. The description reinforces the parameter semantics with examples of stored content ('user's target ticker, an address, prior research notes') and restates the omit-to-list behavior, adding value 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?

The description clearly states the tool's function: 'Retrieve a value previously saved via remember, or list all saved keys (omit the key argument).' It distinguishes from siblings by naming the paired tools: 'Pair with remember to save, forget to delete.' This gives a specific verb, resource, 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?

Explicit when-to-use guidance is provided: 'Use to look up context the agent stored earlier... without re-deriving it from scratch.' It also gives alternatives/contrast with 'remember' and 'forget', and explains the omit-key behavior for listing all saved keys.

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
Disambiguation2/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are variants of the same router, and the six polymarket_* tools cover overlapping arbitrage/edge analysis territory. ai_visibility_check vs scan_competitor_ai_presence and discover_tools vs suggest_questions add further boundary ambiguity. While descriptions try to differentiate, an agent could easily misselect among these clusters.

Naming Consistency3/5

Most names are readable snake_case, but there is no consistent verb_noun pattern: verbs vary (ask, get, list, scan, search, suggest, validate, generate, compare) and several tools are named by product prefix (pipeworx_*, polymarket_*) rather than by action. The pattern is predictable within clusters but inconsistent across the set.

Tool Count2/5

33 tools is heavy for the server's stated name, 'Metals Api', which only has two metals-related tools (get_historical, get_latest). Even as a general data-research server, the surface is bloated with memory utilities, subscription management, feedback, trending, and unrelated AI-visibility scanning. The scope mismatch makes the count feel unjustified.

Completeness3/5

The core metals domain is thin: latest and single-date historical prices exist, but there is no time-series range query, no list of supported metals, and no explicit currency conversion endpoint. The broader data-research/subscription/memory surface is relatively complete, but it is disconnected from the server's apparent purpose, leaving notable gaps for a metals-focused agent.