dart_mcp_core 1.1.3

Production-ready pure Dart core for Model Context Protocol (MCP). Agent execution engine, LLM adapters, MCP client transports, and tool orchestration — no Flutter dependency.

1.1.3

• Upgraded AI SDK Dependencies:
  • Upgraded googleai_dart to ^13.0.0 (Dart SDK >=3.12.0).
  • Upgraded openai_dart to ^10.0.0 (GPT Image 2.5 support, extensible ImageSize value class).
  • Upgraded anthropic_sdk_dart to ^9.0.0 (Dart SDK >=3.12.0).
  • Upgraded ollama_dart to ^4.0.0 (extended thinking union support).

1.1.2

• Conversation Session Resumption & Trajectory Preservation:
  • Added initialMessages property to Agent definition and JSON serialization (toJson / fromJson), allowing multi-turn REPL and CLI agents to save, restore, and continue session transcripts seamlessly.
  • Enhanced AgentFinalResultEvent to carry the full List<ChatMessage> messages trajectory generated across all tool calls and responses during execution.
• Configurable Tool Iteration Limit (maxToolIterations):
  • Added configurable maxToolIterations (default: 100, up from 10) to LlmConfig, Agent, and McpAgentEngine.
  • Added graceful final response synthesis when the tool iteration limit is reached instead of halting execution abruptly.
  • Added automatic recovery prompting if an LLM finishes tool calling with an empty text response.
• Token Usage Reporting & Metric Events:
  • Added AgentUsageEvent stream event to McpAgentEngine providing promptTokens, completionTokens, and totalTokens emitted after each LLM call.
  • Added LLMUsage model attached to LLMResponse capturing usage returned by LLM providers or calculated via fallback token estimation.
• Enhanced Coding Tools:
  • Included full 10-tool autonomous engineering tool suite in CodingTools.createAll(): fs_find, fs_list_dir, fs_read_file, fs_write_file, fs_replace_text, fs_create_dir, fs_move, fs_delete, terminal_exec, and fetch_web.
  • Improved FsReadFileTool with intelligent pagination and safe 800-line chunk truncation, providing clear range hints for large files.
• Bug Fixes:
  • Cleaned up nullable type assertions in OpenAI provider usage mapping.

1.1.0

• New Native Coding Tools & Engine Helpers:
  • Added FsFindTool (fs_find) for discovering files and directories across workspaces with .gitignore awareness.
  • Added FsReadFileTool (fs_read_file) for line-numbered and paginated file inspection.
  • Added FsWriteFileTool (fs_write_file) for creating and overwriting files with automatic directory resolution.
  • Added FsReplaceTextTool (fs_replace_text) for surgical, unique search-and-replace edits.
  • Added TerminalExecTool (terminal_exec) for cross-platform workspace command execution (e.g. dotnet build, dart test, git status).
  • Added CodingTools.createAll() factory helper to bundle coding tools for CLI, Desktop, and Server environments.

1.0.2

• Updated package documentation and branding references to flutter_mcp_suite.

1.0.1

• Expanded LLM SDK dependency version constraints to support anthropic_sdk_dart 9.x, googleai_dart 13.x, openai_dart 9.x, and ollama_dart 3.x.

1.0.0

• Initial stable production release under the flutter_mcp_suite ecosystem.
• Rebranded and modernized from mcp_playground_dart.
• Production-ready Model Context Protocol (MCP) client transports (HTTP/SSE & stdio subprocesses).
• LLM service adapters for OpenAI, Anthropic, Gemini, and Ollama.
• Agent execution loop and tool orchestration engine.

0.3.2

• Upgraded AI SDK dependencies:
  • anthropic_sdk_dart to ^8.0.0
  • googleai_dart to ^12.0.1
  • openai_dart to ^8.1.0
  • ollama_dart to ^2.6.1
  • yaml to ^3.1.4
  • test to ^1.32.0
• New Pure Dart Examples & Skills:
  • Git Staged Diff Reviewer & PR Generator (examples/dart/git_review_skill): Automated git inspection workflow that reads staged diffs, runs static analysis, and produces structured pull request markdown reviews (PR_REVIEW.md).
  • API Endpoint Health & Schema Prober (examples/dart/api_tester_skill): REST health-checking agent benchmarking endpoint latency, validating JSON schema payloads, and generating diagnostic audit reports (API_DIAGNOSTICS.md).
  • SQLite Database Analyst & Executive Reporter (examples/dart/sqlite_analyst_skill): Autonomous database exploration agent that introspects relational schemas, executes aggregation queries, and exports business intelligence summaries (DATABASE_REPORT.md).

0.3.1

• Fixed repository URL in pubspec.yaml to point to GitHub main branch.

0.3.0

• Windows Stdio MCP Server Execution: Switched Windows NPX server launching to direct node.exe execution with npx-cli.js, eliminating cmd.exe stdin pipe stalls during MCP initialize handshakes.
• Mistral Streaming: Fixed _MistralPatchClient buffering live SSE event streams, enabling real-time chunk streaming.
• Added LocalMcpRuntime.findNpxCli and _resolveWindowsExe helpers for robust tool detection on Windows.
• Unified 0.3.0 release across the MCP Playground ecosystem.

0.2.2

• Added SkillImporter.collectNeededTools() — collects all tool names referenced by a skill manifest (declared tools + per-step enabledToolNames).
• Added SkillImporter.buildUnresolvableToolsWarning() — builds a human-readable warning listing missing tools with capability/install/registry details.
• McpAgentEngine.registerAgentFromManifest() now tracks resolved capability tools and emits an AgentLogEvent warning when unresolvable tools are detected.

0.2.1

• Added McpAgentEngine.registerAgentFromManifest() — builds and registers an Agent directly from a parsed SkillManifest, handling tool-declaration → McpServerConfig mapping and prompt-step conversion. Accepts optional dartTools, workingDir, and serverOverrides.
• Updated SkillExporter.toSkillMd() compatibility tag from mcp_playground to "Universal" to match agentskills.io TealKit standard.
• Added dartTools parameter to registerAgentFromManifest() for Dart-native local tool injection (weather, charts, SSH).

0.2.0

• BREAKING: SKILL.md export/import format changed to agentskills.io TealKit-compatible standard (compatibility:, metadata:, workflow:, agents:). Legacy custom format (system_prompt:, prompts:, tools:) is deprecated.
• Added SkillManifest, SkillPromptStep, SkillToolDeclaration models with 3-tier portability (capability, local, external).
• Added SkillExporter — converts SavedPlaygroundSetup/conversation → SKILL.md YAML frontmatter.
• Added SkillImporter — parses SKILL.md (both TealKit and legacy formats) → SavedPlaygroundSetup with multi-prompt step conversion.
• Added SkillStorageAdapter abstract interface with StoredSkillInfo for pluggable skill ZIP persistence.
• Added yaml dependency for robust YAML parsing.

0.1.4

• Upgraded dependencies: anthropic_sdk_dart to ^6.0.0, googleai_dart to ^9.0.0, ollama_dart to ^2.4.0, http to ^1.6.0.

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.