> ## 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. # Retrieve Asset Evaluation Score Batches > Returns asset evaluation scores grouped into batches based on their creation timestamp. Each batch contains the assets scored in a single creation request, identified by the shared `created_at` timestamp. Batches are ordered from newest to oldest. Each asset contains its overall summary, source, content type, and individual attribute scores with their explanations. **When to use:** Retrieve the results of individual scoring batches for an asset evaluation instead of receiving all scores in a single flat list. **Returns:** An object containing the evaluation ID and a list of batches, each with its creation timestamp and associated asset results. ## OpenAPI ````yaml https://openapi.shareofmodel.ai/swagger.json get /v1/organizations/{organization_id}/workspaces/{workspace_id}/asset_evaluations/{evaluation_id}/scores/batches 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 Every read-only (`GET`) endpoint of this specification and of the Search API specification is exposed as an MCP tool, except account administration (API keys, platform integrations and accounts, user roles, favourites, SSO and SCIM). Write endpoints are exposed only when they are marked for agents: creating and pricing brand analyses, Search analyses and GEO audits, creating personas, and managing asset evaluations. Write tools act with the role of the signed-in user, so creating requires the Organization Editor or Owner role, or Workspace Editor in the target workspace. Before creating an analysis or a GEO audit, the assistant shows the full setup and its cost and waits for an explicit confirmation. ### 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."_ - _"Set up a brand analysis for brand A in France."_ 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}/asset_evaluations/{evaluation_id}/scores/batches: get: tags: - Metrics summary: Retrieve Asset Evaluation Score Batches description: >- Returns asset evaluation scores grouped into batches based on their creation timestamp. Each batch contains the assets scored in a single creation request, identified by the shared `created_at` timestamp. Batches are ordered from newest to oldest. Each asset contains its overall summary, source, content type, and individual attribute scores with their explanations. **When to use:** Retrieve the results of individual scoring batches for an asset evaluation instead of receiving all scores in a single flat list. **Returns:** An object containing the evaluation ID and a list of batches, each with its creation timestamp and associated asset results. operationId: retrieve_asset_scores_batches parameters: - in: path name: evaluation_id schema: type: string format: uuid description: A UUID string identifying the asset evaluation. 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: $ref: '#/components/schemas/AssetEvaluationScoresResultsBatches' description: Asset evaluation scores grouped by creation timestamp. '204': description: No asset scores found. security: - Bearer: [] components: schemas: AssetEvaluationScoresResultsBatches: properties: evaluation_id: title: Evaluation Id type: string batches: items: $ref: '#/components/schemas/AssetScoresBatch' title: Batches type: array required: - evaluation_id - batches title: AssetEvaluationScoresResultsBatches type: object AssetScoresBatch: properties: created_at: format: date-time title: Created At type: string assets: items: $ref: '#/components/schemas/AssetResults' title: Assets type: array required: - created_at - assets title: AssetScoresBatch type: object AssetResults: properties: asset_id: title: Asset Id type: string content_type: title: Content Type type: string overall_summary: title: Overall Summary type: string source: title: Source type: string attributes: items: $ref: '#/components/schemas/AttributeResult' title: Attributes type: array required: - asset_id - content_type - overall_summary - source - attributes title: AssetResults type: object AttributeResult: properties: name: title: Name type: string score: title: Score nullable: true type: number explanation: title: Explanation type: string required: - name - score - explanation title: AttributeResult type: object securitySchemes: Bearer: type: apiKey in: header name: Authorization ```` This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.