> ## Documentation Index > Fetch the complete documentation index at: https://docs.shareofmodel.ai/llms.txt > Use this file to discover all available pages before exploring further. # Brand Ownership of Each Theme > Shows which brands dominate each perception theme (cluster), revealing market le adership in specific attributes. For each theme, this endpoint shows what percentage each brand owns. For example, in the 'Comfortable' cluster: Nike 30%, Puma 45%, Adidas 25%. This identifies which brands own which themes in consumers' minds. Perfect for finding category leaders in specific attributes or identifying white space opportunities. **When to use:** User wants to find which brand leads in a specific attribute, identify competitive positioning by theme, discover market gaps in certain perceptions, or understand brand ownership of key themes. **Common user queries:** - "Which brand is strongest in comfort?" - "Who owns the 'affordable' perception?" - "Show me brand leadership by theme" - "Which brands dominate the quality perception?" - "Compare brand positions on style" - "Who are the leaders in each cluster?" **Returns:** Object with cluster names containing brand ownership percentages. Example: {"Comfortable": {"Nike": "0.30", "Adidas": "0.25", "Puma": "0.45"}, "Sporty": {"Nike": "0.20", "Adidas": "0.16", "Puma": "0.64"}} Required permission: `read:analysis`. ## OpenAPI ````yaml https://openapi.shareofmodel.ai/swagger.json get /v1/organizations/{organization_id}/workspaces/{workspace_id}/analyses/{analysis_id}/metrics/brand_perception/brand_share_by_cluster openapi: 3.0.3 info: title: Share Of Model API version: v1 description: >- ## Model Context Protocol (MCP) In addition to this REST API, Share of Model exposes a **Model Context Protocol** server that lets AI assistants (Claude Desktop, Claude Code, MCP Inspector, custom agents…) call our endpoints directly as tools. Any MCP-compatible client can interact with Share of Model without writing custom integration code — connect once with your usual login and start asking the assistant to query the data for you. ### Connecting from Claude Desktop Open **Settings → Connectors**, scroll to the bottom and click **Add custom connector**, then paste `https://mcp.shareofmodel.ai/mcp/`. A browser window opens for you to log in with your Share of Model account (same login as the web app), and the assistant gains access to the tools. ### Connecting from Claude Code ```bash claude mcp add --transport http share-of-model https://mcp.shareofmodel.ai/mcp/ ``` The first time you call a tool, Claude Code opens your browser to complete the login. ### Connecting from MCP Inspector ```bash npx @modelcontextprotocol/inspector ``` In the Inspector UI, pick **Streamable HTTP** as transport, paste `https://mcp.shareofmodel.ai/mcp/`, and click **Connect**. The first connection prompts you to log in. ### Available tools Only endpoints tagged `mcp` in this OpenAPI spec are exposed as MCP tools, and only read-only (`GET`) routes are exposed. Everything tagged `mcp` below is callable from any compliant MCP client. ### Example prompts Once connected, try asking your assistant things like: - _"List the workspaces I have access to."_ - _"Show me the latest searches in workspace X."_ - _"Compare the share of model between brand A and brand B over the last 30 days."_ For more details on the protocol itself, see the [Model Context Protocol specification](https://modelcontextprotocol.io/). servers: - description: Production API url: https://api.shareofmodel.ai/ - description: Development API url: https://api.dev.shareofmodel.ai/ security: [] tags: - name: Auth description: Endpoints needed for API authentication. - name: Organizations description: Endpoints related to organizations, to list all available organizations. - name: Workspaces description: Endpoints related to workspaces, to list all available workspaces. - name: Analyses description: Endpoints related to analyses and analyses management. - name: Asset Evaluations description: Endpoints related to assets and asset evaluations. - name: Brand Catalog description: Endpoints related to general brand information. - name: Content Briefs description: Endpoints related to content briefs generation and optimisation. - name: Metrics description: >+ Endpoints related to brand metrics. **LEXICON** **Brand Awareness**: What opinion the LLMs have concerning specific brands, related to certain categories. **Brand Perception**: The general sentiment of the LLMs towards a brand, based on the pros and cons they mention. paths: /v1/organizations/{organization_id}/workspaces/{workspace_id}/analyses/{analysis_id}/metrics/brand_perception/brand_share_by_cluster: get: tags: - Metrics summary: Brand Ownership of Each Theme description: >- Shows which brands dominate each perception theme (cluster), revealing market le adership in specific attributes. For each theme, this endpoint shows what percentage each brand owns. For example, in the 'Comfortable' cluster: Nike 30%, Puma 45%, Adidas 25%. This identifies which brands own which themes in consumers' minds. Perfect for finding category leaders in specific attributes or identifying white space opportunities. **When to use:** User wants to find which brand leads in a specific attribute, identify competitive positioning by theme, discover market gaps in certain perceptions, or understand brand ownership of key themes. **Common user queries:** - "Which brand is strongest in comfort?" - "Who owns the 'affordable' perception?" - "Show me brand leadership by theme" - "Which brands dominate the quality perception?" - "Compare brand positions on style" - "Who are the leaders in each cluster?" **Returns:** Object with cluster names containing brand ownership percentages. Example: {"Comfortable": {"Nike": "0.30", "Adidas": "0.25", "Puma": "0.45"}, "Sporty": {"Nike": "0.20", "Adidas": "0.16", "Puma": "0.64"}} Required permission: `read:analysis`. operationId: brand_share_by_cluster parameters: - in: path name: analysis_id schema: type: string format: uuid description: A UUID string identifying the analysis. required: true - in: query name: cluster_group schema: type: string enum: - all_cons - all_pros description: Filter by one specific cluster group. required: true - in: query name: collection_date schema: type: string format: date description: >- Filter by a collection date being equal to the specified date. YYYY-MM-DD format - in: query name: collection_date__gt schema: type: string format: date description: >- Filter by a collection date being greater than the specified date. YYYY-MM-DD format - in: query name: collection_date__gte schema: type: string format: date description: >- Filter by a collection date being greater than or equal the specified date. YYYY-MM-DD format - in: query name: collection_date__lt schema: type: string format: date description: >- Filter by a collection date being less than the specified date. YYYY-MM-DD format - in: query name: collection_date__lte schema: type: string format: date description: >- Filter by a collection date being less than or equal the specified date. YYYY-MM-DD format - in: query name: country schema: type: string description: Filter by one specific country. - in: query name: country__in schema: type: string description: >- Filter by a list of countries. Values should be comma separated, without brackets or spaces - in: query name: format schema: type: string enum: - csv - json - in: path name: organization_id schema: type: string format: uuid description: A UUID string identifying the organization. required: true - in: query name: persona schema: type: string description: Filter by one specific persona. - in: query name: persona__in schema: type: string description: >- Filter by a list of personas. Values should be comma separated, without brackets or spaces - in: query name: source schema: type: string enum: - claude-3-5-sonnet - claude-4-5-sonnet - claude-4-6-sonnet - claude-4-sonnet - deepseek-chat - deepseek-reasoner - deepseek-v3.2-maas - gemini-1.5-pro - gemini-2.0-flash - gemini-2.5-flash - gemini-2.5-flash-grounded - gemini-2.5-flash-lite - gemini-3-flash-preview - google-ai-mode - gpt-3.5-turbo - gpt-4-turbo - gpt-4o - gpt-4o-mini-search - gpt-5 - gpt-5.2 - gpt-5.4-mini - meta-llama-3.1-70B-instruct-turbo - meta-llama-3.2-70B-instruct-turbo - meta-llama-3.3-70B-instruct-turbo - meta-llama-4-maverick - mistral-7B-instruct - perplexity-sonar - rufus description: Filter by one specific source. - in: query name: source__in schema: type: string enum: - claude-3-5-sonnet - claude-4-5-sonnet - claude-4-6-sonnet - claude-4-sonnet - deepseek-chat - deepseek-reasoner - deepseek-v3.2-maas - gemini-1.5-pro - gemini-2.0-flash - gemini-2.5-flash - gemini-2.5-flash-grounded - gemini-2.5-flash-lite - gemini-3-flash-preview - google-ai-mode - gpt-3.5-turbo - gpt-4-turbo - gpt-4o - gpt-4o-mini-search - gpt-5 - gpt-5.2 - gpt-5.4-mini - meta-llama-3.1-70B-instruct-turbo - meta-llama-3.2-70B-instruct-turbo - meta-llama-3.3-70B-instruct-turbo - meta-llama-4-maverick - mistral-7B-instruct - perplexity-sonar - rufus description: >- Filter by a list of sources. Values should be comma separated, without brackets or spaces - in: query name: translate_to_en schema: type: boolean description: >- If true, translates clusters and attributes to English. Defaults to false. - in: path name: workspace_id schema: type: string format: uuid description: A UUID string identifying the workspace. required: true responses: '200': content: application/json: schema: type: object description: Cluster name additionalProperties: type: object description: Brand name additionalProperties: type: string format: decimal description: Share of the brand for the cluster examples: ResponseExample: value: Comfortable: Nike: '0.30' Adidas: '0.2500' Puma: '0.4500' Sporty: Nike: '0.20' Adidas: '0.1550' Puma: '0.6450' summary: Response example text/csv: schema: type: object description: Cluster name additionalProperties: type: object description: Brand name additionalProperties: type: string format: decimal description: Share of the brand for the cluster examples: ResponseExample: value: Comfortable: Nike: '0.30' Adidas: '0.2500' Puma: '0.4500' Sporty: Nike: '0.20' Adidas: '0.1550' Puma: '0.6450' summary: Response example description: '' security: - Bearer: [] components: securitySchemes: Bearer: type: apiKey in: header name: Authorization ````