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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

A4.3/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context beyond annotations, such as scoping to an identifier and listing behavior when 'key' is omitted. 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?

The description is three sentences, front-loaded with the core function. Every sentence adds value, and there is no unnecessary information.

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 retrieval tool with no output schema, the description covers purpose, usage, scoping, and interaction with sibling tools. It is thorough and leaves no major 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 coverage is 100% with a single optional 'key' parameter described. The description reinforces the schema ('omitting key lists all keys') and adds examples of potential key values, but does not significantly add new semantic meaning 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 that 'recall' retrieves a value saved via 'remember' or lists all keys if 'key' is omitted. It provides concrete examples of what can be stored (target ticker, address, research notes) and distinguishes itself from sibling tools 'remember' and 'forget' by describing their relationship.

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 previously stored context without re-deriving it. It also mentions scoping to an identifier and pairing with 'remember' and 'forget'. While it doesn't explicitly state when not to use it, the guidance is clear enough for a simple retrieval tool.

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

A3.7/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, creating a true duplicate entry point, and the prediction-market cluster (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread) all detect mispricings with heavily overlapping descriptions. The detailed docs help, but an agent choosing among these will frequently misselect.

Naming Consistency3/5

The set mixes verb-first names (ask_pipeworx, compare_entities, discover_tools, subscribe) with noun-first names (polymarket_edges, entity_profile, ip_context, recent_changes) and bare verbs (remember, forget) without a unifying convention. Subfamilies are internally consistent (polymarket_*, ask_pipeworx_*, subscribe/unsubscribe), which keeps it readable, but there is no predictable server-wide pattern.

Tool Count2/5

32 tools is well into the too-many band, and several tools duplicate or wrap others: ask_pipeworx_beta is a redundant copy of ask_pipeworx, scan_competitor_ai_presence wraps ai_visibility_check, and bet_research overlaps polymarket_edges/arbitrage. The broad scope justifies a large set, but it would be tighter and clearer around 20-24 tools.

Completeness4/5

For the domain the descriptions actually define (structured-data research, company intelligence, prediction markets, subscriptions, memory), coverage is strong with few dead ends: subscription and memory lifecycles are complete, and research has routing/grounded/deep modes. However, the server is named Greynoise while only ip_context serves that domain, and side tools like generate_llms_txt and scan_dependency sit outside any core workflow.