> ## 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. # Audience Gender Demographics > Shows the gender composition of a brand's target audience, indicating male/femal e/all distribution patterns. This endpoint returns the percentage breakdown of audience segments by gender. Reveals whether a brand appeals more to specific genders or has balanced appeal. Essential for understanding gender-based targeting opportunities and adjusting creative messaging. A sports brand might learn their audience is 70% male, indicating potential opportunity to attract more female customers. **When to use:** User wants to understand gender composition, identify gender skew, find underrepresented genders, analyze gender-based targeting, or compare gender appeal across brands. **Common user queries:** - "What's the gender breakdown of Nike's audience?" - "Show me gender distribution" - "Is the audience more male or female?" - "Get gender demographics" - "Compare gender composition across brands" - "What percentage is female?" **Returns:** Array of genders with percentage distribution. Example: [{"gender": "male", "percentage": 55.0}, {"gender": "female", "percentage": 40.0}, {"gender": "all", "percentage": 5.0}] Required permission: `read:analysis`. ## OpenAPI ````yaml https://openapi.shareofmodel.ai/swagger.json get /v1/organizations/{organization_id}/workspaces/{workspace_id}/analyses/{analysis_id}/metrics/target_audience/gender_distribution 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/target_audience/gender_distribution: get: tags: - Metrics summary: Audience Gender Demographics description: >- Shows the gender composition of a brand's target audience, indicating male/femal e/all distribution patterns. This endpoint returns the percentage breakdown of audience segments by gender. Reveals whether a brand appeals more to specific genders or has balanced appeal. Essential for understanding gender-based targeting opportunities and adjusting creative messaging. A sports brand might learn their audience is 70% male, indicating potential opportunity to attract more female customers. **When to use:** User wants to understand gender composition, identify gender skew, find underrepresented genders, analyze gender-based targeting, or compare gender appeal across brands. **Common user queries:** - "What's the gender breakdown of Nike's audience?" - "Show me gender distribution" - "Is the audience more male or female?" - "Get gender demographics" - "Compare gender composition across brands" - "What percentage is female?" **Returns:** Array of genders with percentage distribution. Example: [{"gender": "male", "percentage": 55.0}, {"gender": "female", "percentage": 40.0}, {"gender": "all", "percentage": 5.0}] Required permission: `read:analysis`. operationId: target_audience_gender_distribution 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: 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: 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: 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: 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: $ref: '#/components/schemas/TargetAudienceGenderDistribution' text/csv: schema: type: array items: $ref: '#/components/schemas/TargetAudienceGenderDistribution' description: '' security: - Bearer: [] components: schemas: TargetAudienceGenderDistribution: type: object description: Base class with necessary methods overridden properties: gender: type: string percentage: type: string format: decimal pattern: ^-?\d{0,3}(?:\.\d{0,2})?$ required: - gender - percentage securitySchemes: Bearer: type: apiKey in: header name: Authorization ````