> ## 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. # AI Insights: Brand Ranking Patterns > Returns AI-generated insights about brand ranking positions, explaining which brands consistently appear first vs last in AI recommendations. This endpoint analyzes average position data and generates insights like "Nike holds the top position at 1.2, significantly ahead of Adidas at 2.8, indicating strong top-of-mind awareness." Identifies ranking leaders, laggards, and competitive gaps in recommendation order. **When to use:** User wants interpreted ranking insights, needs to understand position patterns, identifies top-ranked brands, or requires strategic recommendations based on position data. **Common user queries:** - "Generate insights on brand rankings" - "Explain which brands rank highest" - "What do the position numbers mean?" - "Summarize competitive ranking patterns" - "Which brand dominates recommendations?" - "Show ranking insights" **Returns:** Array of insight objects interpreting position data with strategic implications. Current model in use: `gpt-5.4-mini`. Required permission: `read:analysis` ## OpenAPI ````yaml https://openapi.shareofmodel.ai/swagger.json get /v1/organizations/{organization_id}/workspaces/{workspace_id}/analyses/{analysis_id}/insights/brand_awareness/average_position 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}/insights/brand_awareness/average_position: get: tags: - Insights summary: 'AI Insights: Brand Ranking Patterns' description: >- Returns AI-generated insights about brand ranking positions, explaining which brands consistently appear first vs last in AI recommendations. This endpoint analyzes average position data and generates insights like "Nike holds the top position at 1.2, significantly ahead of Adidas at 2.8, indicating strong top-of-mind awareness." Identifies ranking leaders, laggards, and competitive gaps in recommendation order. **When to use:** User wants interpreted ranking insights, needs to understand position patterns, identifies top-ranked brands, or requires strategic recommendations based on position data. **Common user queries:** - "Generate insights on brand rankings" - "Explain which brands rank highest" - "What do the position numbers mean?" - "Summarize competitive ranking patterns" - "Which brand dominates recommendations?" - "Show ranking insights" **Returns:** Array of insight objects interpreting position data with strategic implications. Current model in use: `gpt-5.4-mini`. Required permission: `read:analysis` operationId: get_average_position_insights parameters: - in: path name: analysis_id schema: type: string format: uuid description: A UUID string identifying the analysis. required: true - in: path name: organization_id schema: type: string format: uuid description: A UUID string identifying the organization. required: true - 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/ChartInsight' description: '' security: - Bearer: [] components: schemas: ChartInsight: type: object description: Base class with necessary methods overridden properties: insight_title: type: string insight_description: type: string required: - insight_description - insight_title securitySchemes: Bearer: type: apiKey in: header name: Authorization ````