mcp_playground_dart 0.1.3

Pure Dart core for AI Agent Playground. Agent execution engine, LLM adapters, MCP clients, and tool orchestration — no Flutter dependency.

0.1.3

• Refactored streaming support for Small Language Models (SLMs) and embedded models.
• Added dynamic static delegates embeddedHandler and embeddedStreamHandler to plug on-device inference engines without hard code dependencies.
• Added a new headless CLI example embedded_example demonstrating on-device Hugging Face GGUF model downloading, offline inference, local weather tool execution, and token-by-token terminal stream outputs.

0.1.2

• Expose agentEvents stream in McpAgentEngine and return a reactive event stream from runAsync for asynchronous streaming execution.
• Add support for loading LlmConfig hyperparameters (temperature, maxTokens, topP, topK, repeatPenalty) inside provider clients.
• Isolate local stdio client dependencies from web/wasm builds via default stub conditional imports.
• Protocol and logging compliance updates.

0.1.1

• Fixed WASM and Web compilation by integrating universal_io for subprocess/file wrappers.
• Added pure Dart McpChangeNotifier to core clients to remove Flutter dependencies.
• Added comprehensive self-contained package example for pub.dev.

0.1.0

• Initial release of the pure-Dart core package.
• Built-in multi-LLM SDK adapters (OpenAI, Claude, Gemini, Ollama, Mistral).
• HTTP/SSE stateful Model Context Protocol (MCP) clients with authentication and health-monitoring reconnection.
• Desktop stdio process execution client for Node.js and Python MCP servers.
• Core McpAgentEngine supporting sub-prompt orchestration pipelines, iterative tool loops, and loop-protection.