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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

A4.5/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. The description adds value by clarifying scoping (by identifier) and the behavior when the key is omitted (lists all keys). No contradiction with annotations.

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 sentences, no wasted words. The description is front-loaded with the core action and supplementary details follow efficiently.

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?

The tool is simple (one optional parameter, no output schema), and the description covers retrieval, listing, scoping, and pairing with related tools. No gaps remain for an agent to misuse it.

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 description coverage is 100% with one parameter. The description adds meaning beyond the schema by explaining that omitting the key lists all saved keys, which is not in the schema property description.

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 uses specific verbs ('Retrieve', 'list') and clearly identifies the resource (values saved via 'remember'). It distinguishes from siblings like 'remember' and 'forget' by mentioning them directly.

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 explains when to use the tool ('to look up context the agent stored earlier') and pairs it with 'remember' and 'forget'. It does not explicitly state when not to use it, but for a simple retrieval tool, this is adequate.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but the set includes three very similar `ask_pipeworx` variants that could cause confusion despite detailed descriptions. The Polymarket and memory tools are well-differentiated.

Naming Consistency3/5

Names follow a mix of patterns: some `verb_noun` (ask_pipeworx, compare_entities), some `noun_noun` (entity_profile, polymarket_arbitrage), and some standalone nouns (forget, recall). While readable, the inconsistency is notable.

Tool Count3/5

At 33 tools, the server is on the heavy side for typical MCP servers (3-15 ideal). However, the broad scope covering many data domains partially justifies the count.

Completeness4/5

The tool set covers a wide range of data access and analysis needs, including entity resolution, company profiles, betting analysis, subscriptions, and memory. Minor gaps exist (e.g., no direct tool for editing entities), but overall it's well-rounded.