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Glama

Scryfall

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
Behavior5/5

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

The description adds significant value beyond annotations: it clarifies scoping by identifier, persistence behavior for authenticated vs anonymous sessions (24 hours), and that it stores key-value pairs. Annotations indicate idempotentHint=true and destructiveHint=false, which align with the description. 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 very concise with no wasted words. The first sentence states the core purpose, followed by usage guidance, scope, and pairing info. Every sentence adds value.

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?

Given the tool has only two simple parameters and no output schema, the description is fully sufficient. It covers purpose, usage, scope, persistence, and related tools (recall, forget). No gaps.

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 key and value. The description adds specific examples of key names (subject_property, target_ticker) and states value can be any text, supplementing the schema's generic descriptions.

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 across conversations and sessions, with specific examples like resolved ticker, target address, user preference. It distinguishes from sibling tools (recall, forget) by explicitly pairing with them.

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 ('when you discover something worth carrying forward') and implies when not to (temporary data). It mentions pairing with recall and forget but does not explicitly exclude alternative tools like list_sets or generate_llms_txt.

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

A3.9/5.0
Disambiguation3/5

Most tools have distinct purposes, but the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) plus deep_research creates real boundary confusion, and the six polymarket_* tools overlap enough to require careful reading. The few Scryfall card tools are clearly distinct from the Pipeworx bulk, but the name mismatch adds selection friction.

Naming Consistency4/5

All tool names use snake_case and most follow a verb_noun pattern (get_card, search_cards, resolve_entity, validate_claim). There are deviations like entity_profile, deep_research, and pipeworx_trending, but the nested families (ask_pipeworx*, polymarket_*) are internally consistent and predictable.

Tool Count2/5

35 tools is above the 25+ threshold and is especially mismatched with the server name 'Scryfall', which implies a focused MTG card server. Only 4 of 35 tools relate to Scryfall; the remaining 31 form a sprawling data-research platform that would be more appropriately split into separate servers.

Completeness4/5

The dominant Pipeworx data-research surface is remarkably complete: universal lookup, grounded answers, deep research, entity profiles, comparisons, entity resolution, claim validation, change feeds, subscriptions, memory, and discovery. The Scryfall subset covers core card lookup (search, get by name, random, list sets) but lacks rulings, set details, and card-by-ID lookups, which is a minor gap relative to the server's stated name.

Resources