azure-content-understanding-mcp-server
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The Azure Content Understanding MCP Server integrates Azure Content Understanding capabilities with AI systems through a Model Context Protocol (MCP) server.
The Azure Content Understanding MCP Server is designed to facilitate the integration of Azure's advanced content analysis tools with various AI systems. By leveraging the Model Context Protocol (MCP), this server provides a standardized interface for accessing Azure Content Understanding services. The project is structured into core components, including the ContentUnderstanding.MCP.Server.Stdio for MCP server implementation and ContentUnderstanding.MCP.Tools for content analysis and API integration. The server supports document analysis across multiple file formats, utilizing Azure's Content Understanding service to deliver detailed insights. Users can manage and deploy different analyzers based on specific content types or data requirements, ensuring flexibility and precision in content analysis. The server is built on .NET 9.0 SDK and requires an Azure subscription with Content Understanding service and Azure Blob Storage account for operation.
Features
- Document Analysis: Analyze various file formats using Azure Content Understanding service.
- Multiple Analyzer Support: Retrieve and use different analyzers based on content type or data requirements.
- Standard MCP Interface: Expose content analysis tools through a standardized MCP interface.
- Azure Integration: Seamless integration with Azure Content Understanding API and Blob Storage.
- End-to-End Process: Handles document upload, analysis submission, result retrieval, and cleanup.
Tools
ContentUnderstandingClient
Provides methods for interacting with Azure Content Understanding, including creating and updating analyzers, listing available analyzers, submitting documents for analysis, and retrieving results.
AnalyzeDocument
Handles the end-to-end process of document analysis, including uploading to Azure Blob Storage, submitting for analysis, polling for completion, and returning structured results.