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search_metadata

Locate specific photos and videos by filtering EXIF metadata like city, camera model, date range, or OCR text. Narrow results with favorites, people, tags, albums, and more.

Instructions

Search assets by EXIF metadata fields. Use this when you know specific criteria like city, camera model, or date range. For natural language visual queries (e.g. 'sunset at the beach'), use search_smart instead. For browsing without criteria, use list_assets. Read-only.

Args:
    city: City name from EXIF GPS reverse-geocoding (case-sensitive, e.g. 'Barcelona').
    state: State or region name.
    country: Country name (e.g. 'Spain', 'Egypt').
    make: Camera manufacturer (e.g. 'Apple', 'Canon', 'Sony').
    model: Camera model string (e.g. 'iPhone 14 Pro', 'EOS R5').
    taken_after: ISO date — return only assets captured after this date.
    taken_before: ISO date — return only assets captured before this date.
    is_favorite: If true, only return favorites.
    asset_type: 'IMAGE' or 'VIDEO'. Omit for both.
    ocr: Text recognized inside the image (tickets, signs, documents). Needs
        OCR enabled on the server — check with get_capabilities.
    person_ids: Only assets showing ALL of these people (ids from list_people).
    tag_ids: Only assets carrying these tags (ids from list_tags).
    album_ids: Only assets inside these albums.
    page: Page number, starting from 1 (default 1).
    size: Results per page (1-200, default 50).

Returns: JSON with total match count, current page, and assets array with IDs, filenames, and dates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ocrNo
cityNo
makeNo
pageNo
sizeNo
modelNo
stateNo
countryNo
tag_idsNo
album_idsNo
asset_typeNo
person_idsNo
is_favoriteNo
taken_afterNo
taken_beforeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Changed4 schema fields changedv2.0.2
    • addedInput schema / properties / album_ids
      Added value: +{
      +  "anyOf": [
      +    {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Album Ids"
      +}
    • addedInput schema / properties / ocr
      Added value: +{
      +  "default": "",
      +  "title": "Ocr",
      +  "type": "string"
      +}
    • addedInput schema / properties / person_ids
      Added value: +{
      +  "anyOf": [
      +    {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Person Ids"
      +}
    • addedInput schema / properties / tag_ids
      Added value: +{
      +  "anyOf": [
      +    {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Tag Ids"
      +}
  2. First observedv1.0.0

TDQS

A4.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explicitly declares 'Read-only,' discloses a server-side prerequisite for the ocr parameter ('Needs OCR enabled on the server — check with get_capabilities'), and notes case-sensitivity for city. It also describes the return shape. Missing are filter-combination semantics (AND vs OR across fields) and sorting behavior, but the key behavioral traits are disclosed.

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 cleanly organized: a purpose-and-routing paragraph, a complete Args list covering all 15 parameters, and a one-line Returns note. Every sentence earns its place, and the length is fully justified given that the schema provides zero descriptions for the parameters. Information is front-loaded with purpose before detail.

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 high-complexity tool (15 optional parameters, no annotations, 0% schema coverage), the description covers everything needed to call it correctly: purpose, routing, all parameter semantics, return format, and the OCR prerequisite. An output schema exists, so return values need no further elaboration. The only implicit detail is cross-filter AND combination, which is minor given the 'only' qualifiers on each filter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must fully compensate — and it does. Every one of the 15 parameters gets meaning, format hints, and often concrete examples ('Barcelona', 'iPhone 14 Pro', 'EOS R5'). It clarifies case-sensitivity, ISO date semantics, the ALL-matching rule for person_ids, omit-for-both behavior for asset_type, and the 1-200 range for size. This is exemplary compensation for a zero-coverage 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 states 'Search assets by EXIF metadata fields' — a specific verb, resource, and mechanism. It further distinguishes itself from siblings by name: search_smart for natural language visual queries and list_assets for browsing without criteria. An agent can pick this tool correctly without opening any schema.

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?

The description explicitly says 'Use this when you know specific criteria like city, camera model, or date range' and then gives named alternatives with conditions: 'For natural language visual queries... use search_smart instead. For browsing without criteria, use list_assets.' This is textbook when/when-not/alternatives guidance.

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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