The AI Management Module supports MCP (Model Context Protocol), enabling AI workspaces to use external MCP servers as tools. MCP allows AI models to interact with external services, databases, APIs, and more through a standardized protocol.

You can test the connection to an MCP server after creating it to verify connectivity and list available tools before use.

When a workspace has MCP servers associated, the AI model can invoke tools from those servers during chat conversations. Tool calls and results are displayed in the chat interface.

The AI Management module supports RAG (Retrieval-Augmented Generation) with file upload, which enables workspaces to answer questions based on the content of uploaded documents. When RAG is configured, the AI model searches the uploaded documents for relevant information before generating a response. To enable RAG, configure an embedder (e.g., OpenAI, Ollama) and a vector store (e.g., PgVector) on the workspace.

Upload documents (PDF, Markdown, or text files, max 10 MB) through the workspace management UI. Uploaded documents are automatically processed - their content is chunked, embedded, and stored in the configured vector store.

A Workflow module that integrates Elsa Workflows to build visual, long-running, event-driven workflows in your ABP solutions (monolith or microservices). It provides seamless integration with ABP authentication/authorization, distributed event bus, persistence, background processing and includes support for hybrid UIs via Elsa Studio.

Excel export capabilities in the Audit Logging Module allow administrators to export audit logs and entity changes to Excel files for further analysis or reporting purposes.