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Glama

Kroger

by io.github.pipeworx-io

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Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Description adds beyond annotations: key-value pair scoped by identifier, persistence differences per auth status. Annotations already indicate idempotentHint=true and non-destructive, which is consistent. The added behavioral details are valuable.

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 concise and front-loaded: purpose first, then usage guidelines, then persistence details. Every sentence adds value without redundancy.

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?

Despite no output schema, the description covers storage behavior, scoping, persistence, and pairing with sibling tools. It provides all necessary context for an agent to use this tool effectively.

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 descriptions for both parameters. The description adds real-world naming conventions (e.g., 'subject_property') and clarifies value type as 'any text', enhancing 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 'Save data the agent will need to reuse later' with a specific verb and resource. It differentiates from siblings like recall and forget, and provides concrete examples (resolved ticker, target address, etc.).

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?

Explicitly states when to use: 'when you discover something worth carrying forward'. Names sibling tools for complementary actions (recall, forget), providing clear context for usage.

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

All Kroger toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research all query data), making it hard for an agent to choose the correct one. Additionally, entity_profile and compare_entities both provide company profiles, adding further ambiguity.

Naming Consistency2/5

Tool names are inconsistent: some use verb_noun (ask_pipeworx, compare_entities), some noun_verb (entity_profile), and some are single verbs (forget, recall). There is no clear pattern, and the mix of styles (e.g., kroger_*, polymarket_*, pipeworx_*) adds confusion.

Tool Count3/5

34 tools is on the higher end, but the server covers a broad domain (grocery, data query, betting, subscriptions). However, the presence of multiple similar query tools (e.g., three ask_pipeworx variants) inflates the count unnecessarily, making it feel bloated.

Completeness3/5

For its stated Kroger grocery focus, the tools (search, details, store locator) are complete. However, the server also includes many unrelated tools (betting, entity profiles, subscriptions) that feel tacked on, leaving gaps in coverage for the non-Kroger domains (e.g., no tools for user management or other store chains).

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