Implement SEP-1577: Sampling With Tools #1594
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Add support for tool calling during sampling requests, enabling MCP servers to execute agentic workflows using client LLM capabilities. Key changes: - Add ToolUseContent type for assistant tool invocation requests - Add ToolResultContent type for tool execution results - Add ToolChoice type to control tool usage behavior - Add UserMessage and AssistantMessage types for role-specific messages - Extend SamplingMessage to support tool content (backward compatible) - Add SamplingToolsCapability for capability negotiation - Update CreateMessageRequestParams with tools and toolChoice fields - Update CreateMessageResult to support tool use content - Update StopReason to include "toolUse" value - Add comprehensive unit tests for all new types The implementation maintains backward compatibility by keeping SamplingMessage as a flexible BaseModel while adding more specific UserMessage and AssistantMessage types for type-safe tool interactions. All new types follow existing patterns: - Use Pydantic V2 BaseModel - Allow extra fields with ConfigDict(extra="allow") - Include proper docstrings and field descriptions - Support optional fields where appropriate Github-Issue: #1577
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Note: don't merge before the SEP is accepted (currently under review)
Add support for tool calling during sampling requests, enabling MCP servers to execute agentic workflows using client LLM capabilities.
modelcontextprotocol/modelcontextprotocol#1577
Key changes:
The implementation maintains backward compatibility by keeping SamplingMessage as a flexible BaseModel while adding more specific UserMessage and AssistantMessage types for type-safe tool interactions.
All new types follow existing patterns: