Adds comprehensive Model Context Protocol (MCP) integration to Spring AI, including:
Core Features:
- MCP client implementation with Spring AI tool calling capabilities
- Spring-friendly abstractions for MCP clients and servers
- Both synchronous and asynchronous MCP server operation modes
- Add MCP client autoconfiguration with support for STDIO, WebMVC and WebFlux transports
- Auto-configuration for MCP server components
- Spring Boot starter (spring-ai-starter-mcp) with WebFlux and WebMVC support
- MCP dependency management with BOM
- Add close() method to McpToolCallback for proper resource cleanup
- Add initialize flag to control MCP client initialization
- Add comprehensive integration tests and documentation for MCP client configuration
Technical Improvements:
- Split WebMvc and WebFlux configurations into separate auto-configuration classes
- Server type configurable via 'spring.ai.mcp.server.type' property (SYNC/ASYNC)
- Comprehensive test coverage including McpServerAutoConfigurationIT
- Utility classes for converting between Spring AI tools and MCP tools
- MCP SDK version management in parent pom
Reorganize MCP tool utilities and client configuration
- Rename ToolUtils to McpToolUtils for better MCP-specific naming
- Rename McpToolCallbackProvider to SyncMcpToolCallbackProvider
- Add utility methods for handling tool callbacks in McpToolUtils
- Extract client configuration logic into new McpClientDefinitions class
- Add tool callback support to ChatClient interface and implementations
- Remove redundant integration test
Introduce MCP client customization support
- Add McpSyncClientCustomizer interface for customizing MCP sync clients
- Replace McpClientDefinitions with McpSyncClientConfigurer
- Refactor MCP client initialization to support customization
- Remove redundant close() method from McpToolCallback
- Fix conditional class dependencies in WebMvc/Flux configurations
Add MCP AOT hints
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
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