> ## 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 Perception by LLM Source > Shows how a brand's perception themes vary across different AI models (ChatGPT, Gemini, Claude, etc.), revealing consistency or divergence in brand perception. This endpoint breaks down a specific brand's cluster distribution by each AI source/LLM. For example, ChatGPT might perceive Nike as 70% comfortable while Gemini sees it as only 10% comfortable. Critical for identifying perception inconsistencies across different AI platforms and understanding which LLMs favor which brand attributes. **When to use:** User wants to analyze perception consistency across AI models, identify which LLMs have different brand perceptions, compare ChatGPT vs Gemini brand profiles, or validate brand positioning across multiple sources. **Common user queries:** - "How does Nike's perception differ between ChatGPT and Gemini?" - "Show me cluster breakdown by LLM" - "Compare brand perception across AI sources" - "Which AI model sees Nike as most comfortable?" - "Is brand perception consistent across different LLMs?" - "Get source-specific cluster distribution" **Returns:** Array of objects with brand, source, cluster, and share percentages. Example: [{"brand": "Nike", "source": "chatgpt-4", "cluster": "Comfortable", "share": "0.70"}, {"brand": "Nike", "source": "gemini", "cluster": "Comfortable", "share": "0.10"}] 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_cluster_share_by_source 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_cluster_share_by_source: get: tags: - Metrics summary: Brand Perception by LLM Source description: >- Shows how a brand's perception themes vary across different AI models (ChatGPT, Gemini, Claude, etc.), revealing consistency or divergence in brand perception. This endpoint breaks down a specific brand's cluster distribution by each AI source/LLM. For example, ChatGPT might perceive Nike as 70% comfortable while Gemini sees it as only 10% comfortable. Critical for identifying perception inconsistencies across different AI platforms and understanding which LLMs favor which brand attributes. **When to use:** User wants to analyze perception consistency across AI models, identify which LLMs have different brand perceptions, compare ChatGPT vs Gemini brand profiles, or validate brand positioning across multiple sources. **Common user queries:** - "How does Nike's perception differ between ChatGPT and Gemini?" - "Show me cluster breakdown by LLM" - "Compare brand perception across AI sources" - "Which AI model sees Nike as most comfortable?" - "Is brand perception consistent across different LLMs?" - "Get source-specific cluster distribution" **Returns:** Array of objects with brand, source, cluster, and share percentages. Example: [{"brand": "Nike", "source": "chatgpt-4", "cluster": "Comfortable", "share": "0.70"}, {"brand": "Nike", "source": "gemini", "cluster": "Comfortable", "share": "0.10"}] Required permission: `read:analysis`. operationId: brand_cluster_share_by_source parameters: - in: path name: analysis_id schema: type: string format: uuid description: A UUID string identifying the analysis. required: true - in: query name: brand schema: type: string description: Filter by one specific brand. 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: array items: type: object properties: brand: type: string source: type: string enum: - gpt-3.5-turbo - gpt-4-turbo - gpt-4o - gpt-4o-mini-search - gpt-5 - gpt-5.2 - gpt-5.4-mini - gemini-1.5-pro - gemini-2.0-flash - gemini-2.5-flash-grounded - gemini-2.5-flash - gemini-2.5-flash-lite - gemini-3-flash-preview - 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 - claude-3-5-sonnet - claude-4-sonnet - claude-4-5-sonnet - claude-4-6-sonnet - deepseek-chat - deepseek-reasoner - deepseek-v3.2-maas - perplexity-sonar - rufus - google-ai-mode cluster: type: string share: type: string format: decimal required: - brand - source - cluster - share examples: ResponseExample: value: - brand: Nike source: chatgpt-3.5 cluster: Comfortable share: '0.3000' - brand: Nike source: chatgpt-3.5 cluster: Durable share: '0.2000' - brand: Nike source: chatgpt-3.5 cluster: Stylish share: '0.5000' - brand: Nike source: chatgpt-4 cluster: Comfortable share: '0.7000' - brand: Nike source: chatgpt-4 cluster: Durable share: '0.2000' - brand: Nike source: chatgpt-4 cluster: Stylish share: '0.1000' - brand: Nike source: gemini cluster: Comfortable share: '0.1000' - brand: Nike source: gemini cluster: Durable share: '0.7600' - brand: Nike source: gemini cluster: Stylish share: '0.1400' summary: Response example text/csv: schema: type: array items: type: object properties: brand: type: string source: type: string enum: - gpt-3.5-turbo - gpt-4-turbo - gpt-4o - gpt-4o-mini-search - gpt-5 - gpt-5.2 - gpt-5.4-mini - gemini-1.5-pro - gemini-2.0-flash - gemini-2.5-flash-grounded - gemini-2.5-flash - gemini-2.5-flash-lite - gemini-3-flash-preview - 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 - claude-3-5-sonnet - claude-4-sonnet - claude-4-5-sonnet - claude-4-6-sonnet - deepseek-chat - deepseek-reasoner - deepseek-v3.2-maas - perplexity-sonar - rufus - google-ai-mode cluster: type: string share: type: string format: decimal required: - brand - source - cluster - share examples: ResponseExample: value: - brand: Nike source: chatgpt-3.5 cluster: Comfortable share: '0.3000' - brand: Nike source: chatgpt-3.5 cluster: Durable share: '0.2000' - brand: Nike source: chatgpt-3.5 cluster: Stylish share: '0.5000' - brand: Nike source: chatgpt-4 cluster: Comfortable share: '0.7000' - brand: Nike source: chatgpt-4 cluster: Durable share: '0.2000' - brand: Nike source: chatgpt-4 cluster: Stylish share: '0.1000' - brand: Nike source: gemini cluster: Comfortable share: '0.1000' - brand: Nike source: gemini cluster: Durable share: '0.7600' - brand: Nike source: gemini cluster: Stylish share: '0.1400' summary: Response example description: '' security: - Bearer: [] components: securitySchemes: Bearer: type: apiKey in: header name: Authorization ````