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met-museum-mcp-server

Server Details

MET Museum collection via MCP — 500K+ artworks, metadata, provenance, open-access images.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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MCP server

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Tool DescriptionsA

Average 4.7/5 across 3 of 3 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool serves a distinct function: listing departments, searching the collection, and fetching full object records. There is no overlap in their purposes.

Naming Consistency5/5

All tools follow a consistent `met_verb_noun` pattern (met_list_departments, met_search, met_get_object), making it easy to predict tool names.

Tool Count5/5

Three tools cover the essential operations for a read-only museum API—discover, search, and retrieve. The scope is well-defined and neither too sparse nor excessive.

Completeness5/5

The tool set provides full coverage for accessing Met Museum data: discover departments, search with filters, and retrieve full object records. No obvious gaps are present for the intended use case.

Available Tools

3 tools
met_get_objectGet Met ObjectsA
Read-onlyIdempotent
Inspect

Fetch full records for one or more Met Museum object IDs. Accepts up to 20 IDs per call, fetches in parallel (concurrency-limited), and returns partial-success — a single 404 does not fail the whole batch. Object IDs come from met_search. Non-public-domain objects return empty image URLs. The constituents array is null for anonymous or unattributed works; tags is null for untagged objects.

ParametersJSON Schema
NameRequiredDescriptionDefault
objectIDsYesOne or more Met object IDs to fetch. Maximum 20 per call. IDs come from met_search. Fetches run in parallel (concurrency-limited); partial failures are reported per ID rather than failing the whole batch.

Output Schema

ParametersJSON Schema
NameRequiredDescription
failedYesObject IDs that failed to fetch with per-ID error context.
objectsYesSuccessfully fetched objects.
Behavior5/5

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

The description adds significant behavioral details beyond the readOnly and idempotent annotations: parallel fetching with concurrency limits, partial-success handling (404 doesn't fail batch), null image URLs for non-public-domain, null constituents for anonymous works, and null tags for untagged objects. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that efficiently conveys the main purpose and key behaviors. It is not verbose, though it could be slightly more concise by combining some details. Front-loads the core function.

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 that an output schema exists, the description does not need to explain return values. It covers constraints, edge cases (null fields, partial success), and dependencies on met_search. All relevant aspects are addressed.

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%, so baseline is 3. The description adds value by explaining that fetching is parallel and concurrency-limited, and that partial failure is handled per ID. This provides context beyond the 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 it fetches full records for Met Museum object IDs. It specifies the source of IDs (met_search), constraints (up to 20 IDs), and distinguishes from sibling tools by focusing on retrieval rather than search or listing.

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 indicates when to use this tool (after obtaining IDs from met_search) and describes constraints (max 20 IDs, parallel fetching, partial success). It does not explicitly state when not to use, but context from sibling tools implies appropriate usage.

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

met_list_departmentsList Met DepartmentsA
Read-onlyIdempotent
Inspect

Return the 19 curatorial departments at The Metropolitan Museum of Art with their numeric IDs and display names. Use before calling met_search to discover valid departmentId values. The department list is fetched live on each call to remain accurate if the Met reorganizes.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
departmentsYesAll 19 curatorial departments at The Metropolitan Museum of Art.
Behavior5/5

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

Annotations already indicate readOnly and idempotent. Description adds context that the department list is fetched live each call, ensuring accuracy if the Met reorganizes, which goes beyond 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?

Three concise sentences, front-loaded with purpose, no wasted words.

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 no parameters and presence of an output schema, the description fully covers what the tool returns (departments with IDs and display names) and its purpose, making it complete.

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?

No parameters exist, so baseline 4 is appropriate. Description adds no param info because none needed.

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 it returns the 19 curatorial departments with numeric IDs and display names, and distinguishes from siblings by positioning it as a prerequisite for met_search to discover valid departmentId values.

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?

Explicitly says to use before calling met_search to get valid departmentId values, and notes the live fetch for accuracy. Does not explicitly state when not to use, but context is clear.

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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