> ## 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. # List Pros and Cons Cluster Groups > Lists all available cluster groups (themes) for a brand analysis, showing both p ositive (pros) and negative (cons) perception clusters. Clusters are the main themes that emerge from brand mentions, such as 'comfortable', 'expensive', 'durable', 'stylish'. This endpoint returns the names of all available clusters grouped by sentiment (pros vs cons). Use this as a starting point to understand what perception themes exist in the analysis before diving into detailed metrics. **When to use:** User wants to see what clusters exist, explore available themes, understand the structure of pros and cons categories, or get cluster names before querying specific metrics. **Common user queries:** - "What are the pros and cons clusters for this analysis?" - "List all available clusters" - "Show me the themes" - "What cluster groups exist?" - "Get cluster names for Nike" - "What are the strengths and weaknesses themes?" **Returns:** Array of cluster groups with their cluster names. Example: [{"cluster_group": "all_pros", "clusters": ["comfortable", "sporty", "style"]}, {"cluster_group": "all_cons", "clusters": ["expensive", "limited availability"]}] 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/cluster_groups 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/cluster_groups: get: tags: - Metrics summary: List Pros and Cons Cluster Groups description: >- Lists all available cluster groups (themes) for a brand analysis, showing both p ositive (pros) and negative (cons) perception clusters. Clusters are the main themes that emerge from brand mentions, such as 'comfortable', 'expensive', 'durable', 'stylish'. This endpoint returns the names of all available clusters grouped by sentiment (pros vs cons). Use this as a starting point to understand what perception themes exist in the analysis before diving into detailed metrics. **When to use:** User wants to see what clusters exist, explore available themes, understand the structure of pros and cons categories, or get cluster names before querying specific metrics. **Common user queries:** - "What are the pros and cons clusters for this analysis?" - "List all available clusters" - "Show me the themes" - "What cluster groups exist?" - "Get cluster names for Nike" - "What are the strengths and weaknesses themes?" **Returns:** Array of cluster groups with their cluster names. Example: [{"cluster_group": "all_pros", "clusters": ["comfortable", "sporty", "style"]}, {"cluster_group": "all_cons", "clusters": ["expensive", "limited availability"]}] Required permission: `read:analysis`. operationId: cluster_groups 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: 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: cluster_group: type: string clusters: type: array items: type: string required: - cluster_group - clusters examples: ResponseExample: value: - cluster_group: all_cons clusters: - quality - price - reach - cluster_group: all_pros clusters: - comfortable - sporty - style summary: Response example description: '' security: - Bearer: [] components: securitySchemes: Bearer: type: apiKey in: header name: Authorization ````