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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

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. The description adds valuable context: scoping to user identifier and pairing with remember/forget, which goes 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?

Four sentences, each carrying essential information. No fluff. Front-loaded with the core action.

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?

Complete for a read-only lookup tool. Explains behavior with and without key, scoping, and relationship to sibling tools. No output schema needed as the return is obvious.

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% with a description for 'key'. The description adds clarity by explaining the effect of omitting the argument (list all keys) and provides real-world examples like 'user's target ticker'.

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 tool retrieves a previously saved value or lists all keys when omitted. The verb 'retrieve' and resource 'memory' are explicit, and it distinguishes from sibling tools '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?

Provides explicit context: 'Use to look up context the agent stored earlier... without re-deriving it from scratch.' It implies when not to use (when you need new data), but does not explicitly state exclusions or list alternatives beyond mentioning pair tools.

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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Glama MCP Gateway

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TDQS

A3.9/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates, while deep_research, discover_tools, and suggest_questions blur the line between routing, research, and discovery. The six polymarket_* tools plus bet_research also create a dense cluster where agents could easily select the wrong one. Individual descriptions are detailed, but the set boundaries are not crisp.

Naming Consistency4/5

Names are mostly consistent lowercase snake_case with a verb-first pattern such as list_locations, search_datasets, resolve_entity, and validate_claim. A few exceptions like dataset_details, entity_profile, and pipeworx_trending break the verb_noun convention, but the style is predictable and readable overall.

Tool Count2/5

35 tools is heavy for a single MCP server, especially when several are explicitly redundant (ask_pipeworx_beta) or near-overlapping meta-routers. The count feels inflated by duplicated capabilities and a large prediction-market family rather than by genuinely distinct operations.

Completeness3/5

The broad Pipeworx surface is fairly complete: entity profiles, comparisons, claim verification, memory, subscriptions, and grounded lookups are all represented. However, the server is named Hdx and the actual HDX-specific surface is thin — search_datasets and dataset_details exist, but there is no organization detail, no resource download flow, and no way to manage HDX data beyond browsing.