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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

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. Description adds scoping to identifier and listing behavior when key omitted, which adds value 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences, each with distinct purpose: operation, usage guidance, and contextual details. No redundant words.

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?

For a simple read-only tool with one optional parameter and robust annotations, description covers purpose, usage, scoping, and sibling relationships. Missing return format details but not critical.

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% with clear description for the 'key' parameter. Description essentially restates the schema, adding no new semantic meaning.

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 verb 'retrieve' and 'list', resource 'value' and 'saved keys', and distinguishes from siblings 'remember' and 'forget'.

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?

Explicitly says 'Use to look up context the agent stored earlier... without re-deriving it from scratch', provides scoping info, and pairs with related tools. No explicit exclusion of alternatives but clear enough.

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

A3.5/5.0
Disambiguation2/5

Several tool clusters have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same 5,724 tools with only subtle behavioral differences, and bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_kalshi_spread heavily overlap around prediction-market opportunity discovery. entity_profile, compare_entities, and recent_changes also fan out across the same SEC/news/patent sources, making selection ambiguous for agents.

Naming Consistency2/5

Naming mixes multiple conventions: snake_case verb_noun for odds tools (get_events, list_sports), vendor-prefixed clusters (ask_pipeworx_*, pipeworx_*, polymarket_*), and a few reversed noun-verb names like bet_research. CamelCase is used in ai_visibility_check and generate_llms_txt adds another style. Only the polymarket_* and pipeworx_* families are internally consistent, but the overall pattern is chaotic.

Tool Count2/5

37 tools is well beyond the typical well-scoped server, and the count feels inflated by unrelated meta-tools (suggest_questions, discover_tools, pipeworx_feedback, pipeworx_trending, generate_llms_txt, scan_dependency, remember/recall/forget) that have nothing to do with the server's stated 'Odds Api' purpose. The actual odds surface is only ~5 tools, so the vast majority of the catalog is off-scope padding.

Completeness3/5

The core odds domain is well covered: list_sports, get_events, get_odds, get_event_odds, and get_scores form a coherent lifecycle, plus quota introspection. However, for the server's actual broad-research scope there are noticeable gaps (e.g., no direct single-filing fetch tool despite heavy SEC coverage, a lone npm-dependency tool with no surrounding ecosystem, and no historical/past-odds endpoint), and the heterogeneous domains make completeness uneven.