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Discovery tools help AI agents discover and understand available content types, existing content, components, and media assets within a project.

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Available Tools

search_content_types

Search for content types

get_content_type

Get complete content type schema

search_content

Search for content items

get_content

Get complete content details

list_components

List and search components

search_assets

Search for media assets

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Search Modes

All search tools support two modes:

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Semantic Search (with query)

When you include a query parameter, the tool uses AI-powered vector search:
  • Results are ranked by semantic relevance
  • Finds items based on meaning, not just keywords
  • Returns excerpt and similarity fields
  • Best for natural language queries like “content about product launches”

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Standard Filtering (without query)

When you omit the query parameter, the tool uses exact matching:
  • Results are filtered by the specified criteria
  • Returns consistently ordered results
  • No excerpt or similarity fields
  • Best for browsing by type, status, or tags
Combine semantic search with filters for precise results. For example, search for “hero banner” within the view component type to find relevant display components.

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Common Workflow

// 1. Search for content types to understand what structures are available
const types = await mcp.call("search_content_types", {
  query: "blog posts"
});

// 2. Get the full schema for the content type you want to use
const schema = await mcp.call("get_content_type", {
  contentTypeId: types.contentTypes[0].id
});

// 3. Search for existing content as examples
const content = await mcp.call("search_content", {
  typeId: schema.id,
  limit: 5
});

// 4. Find assets to use in new content
const assets = await mcp.call("search_assets", {
  query: "hero image",
  type: "image/*"
});