Skip to main content
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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it explains that results are 'scoped to your identifier (anonymous IP, BYO key hash, or account ID)', which is a meaningful behavioral trait not captured in the schema or 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?

The description is two sentences, front-loaded with the primary action and mode, followed by usage context and scope. Every sentence conveys necessary information without waste, and the structure is easy to parse for an agent.

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?

This is a simple tool with one optional parameter, no output schema, and rich annotations. The description covers purpose, modes, usage context, scope, and sibling relationships, which is fully sufficient for an agent to select and invoke the tool correctly. No critical information is missing.

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?

The schema already provides 100% coverage for the single 'key' parameter, including the 'omit to list all keys' behavior. The description echoes this same semantic, adding illustrative examples but no new technical details. With high schema coverage, the baseline is 3, and the description does not exceed that baseline.

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 with a specific verb ('Retrieve') and resource ('a value previously saved via remember'), plus a distinct secondary mode ('list all saved keys' when key omitted). It also explicitly distinguishes itself from sibling tools 'remember' and 'forget', making it unambiguous.

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?

The description provides concrete use cases ('the user's target ticker, an address, prior research notes') and explains when to use the tool ('without re-deriving it from scratch'). It directly mentions the complementary sibling tools 'remember' and 'forget', effectively guiding the agent on when to use this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Many tools have overlapping or unclear purposes, e.g., multiple entity research tools (entity_profile, recent_changes, compare_entities, validate_claim) and several betting tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread). The memory tools (remember, recall, forget) and generic lookup tools (ask_pipeworx, discover_tools) further blur boundaries, making it hard for an agent to consistently select the right tool.

Naming Consistency2/5

Tool names follow no consistent pattern: some use snake_case verbs (forget, recall, remember), others are noun phrases (entity_profile, recent_changes), and many have mixed conventions (ai_visibility_check, ask_pipeworx, bet_research). There is no clear verb_noun structure, and the naming style varies widely across the set.

Tool Count3/5

At 22 tools, the count is within a reasonable range, but the server's stated purpose ('Geoboundaries') is severely mismatched with the actual tool set, which covers data retrieval, betting, memory, and more. The number is not excessive for the breadth of functionality, but it feels bloated for a server that should be focused on geographic boundaries.

Completeness1/5

The server is named 'Geoboundaries' but only provides two boundary-related tools (get_boundaries, get_geometry). The remaining 20 tools are unrelated, covering general data access, betting arbitrage, and memory operations. This leaves massive gaps for the implied domain (no tools for boundary editing, search by location, or other geographic operations) while over-supplying tools for unrelated tasks.