Skip to main content
Glama

Metmuseum

by io.github.pipeworx-io

Remember

remember
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)

TDQS

A4.6/5.0
Behavior5/5

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

Discloses behavioral traits beyond annotations: key-value pair scoped by identifier, persistent for authenticated users, 24-hour retention for anonymous sessions. Annotations already indicate idempotent and non-destructive; description adds valuable context.

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 sentences, front-loaded with main purpose, no wasted words. Efficiently conveys all necessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple key-value store tool, description covers purpose, usage, persistence, and pairing. Lacks details on overwrite behavior but idempotent annotation hints at it. No output schema, but return value is not critical.

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?

Schema description coverage is 100%, so baseline is 3. Description adds no extra meaning beyond schema examples; schema already provides key and value descriptions with examples.

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?

Description clearly states the tool saves data for reuse later, using specific verb 'save' and resource 'data'. It distinguishes itself from sibling tools 'recall' and 'forget' by mentioning them explicitly.

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?

Provides explicit guidance on when to use (discover something worth carrying forward) and when not (not needed for single-use data). Mentions alternatives ('recall' to retrieve, 'forget' to delete) and scoping rules.

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

All Metmuseum toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

The server mixes two Met-specific tools (get_artwork, search_artworks) with a large set of generic Pipeworx tools (ask_pipeworx, bet_research, etc.), making it unclear which tools actually relate to the Met museum. Agents will struggle to distinguish the domain-specific tools from the general data tools.

Naming Consistency2/5

Tool names follow no consistent pattern: Met-specific tools use get_/search_/list_ prefixes, while Pipeworx tools use diverse patterns (ask_, bet_, compare_, discover_) and some use underscores while others lack verbs. The inconsistency increases cognitive load.

Tool Count3/5

At 29 tools, the count is high but not unreasonable for a combined server. However, only 3 tools are Met-specific, so the count feels inflated by unrelated tools. A more focused Met server would have fewer tools.

Completeness2/5

For a Met museum server, the tool surface is severely limited: only search, get by ID, and list departments. Missing operations like filtering by artist, retrieving related objects, or accessing collection highlights. The domain coverage is incomplete.

Resources