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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

A4.9/5.0
Behavior5/5

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

Description adds scoping by identifier and persistence differences (authenticated vs anonymous) beyond annotations, which already indicate idempotent and non-destructive behavior.

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 well-structured sentences: purpose, usage context, technical details. No redundant information; every sentence is essential.

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 two-param tool with no output schema, the description covers purpose, when to use, technical details, and pairing with sibling tools. Complete and self-contained.

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 has 100% description coverage, but description provides helpful examples (subject_property, target_ticker) and clarifies key purpose and value content, adding meaning beyond 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 the tool saves data for reuse, specifies the verb 'save' and resource 'data', and distinguishes from siblings recall and forget with concrete examples.

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 says when to use ('when you discover something worth carrying forward'), provides context (across conversations/sessions), and pairs with recall/forget for complete workflow.

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

B3.3/5.0
Disambiguation1/5

The vast majority of tools (e.g., ask_pipeworx, ask_pipeworx_grounded, bet_research, polymarket_arbitrage, etc.) are unrelated to Metabolights and overlap heavily with each other in purpose. Only two tools (get_study and search_studies) are clearly distinct and relevant to the server's stated domain.

Naming Consistency2/5

Tool names are highly inconsistent, mixing snake_case (get_study, search_studies), camelCase (ask_pipeworx), and varied verb styles (e.g., validate_claim vs bet_research). No consistent pattern across the set.

Tool Count1/5

With 28 tools, the server is extremely overpopulated for its stated purpose (Metabolights). Only 2 tools actually pertain to metabolomics study access, while the remaining 26 are general-purpose or unrelated (e.g., bet_research, polymarket_edges), making the count highly inappropriate.

Completeness1/5

The Metabolights domain severely lacks completeness: only search_studies and get_study are provided, with no create, update, delete, or upload functionality. The server fails to cover essential operations for its supposed domain.