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Whether you're debugging code, planning architecture, writing tests, or having a technical discussion, SAGE automatically selects the right approach and model for optimal results.\n\n## ✨ Key Features\n\n### 🎯 **Intelligent Mode System**\n- **chat** - Natural conversations with context awareness\n- **analyze** - Deep code analysis and pattern recognition  \n- **review** - Comprehensive code reviews with actionable feedback\n- **debug** - Systematic debugging and root cause analysis\n- **plan** - Strategic project planning and architecture design\n- **test** - Test generation with coverage analysis\n- **refactor** - Code improvement and modernization\n- **think** - Deep reasoning with adjustable thinking depth\n\n### 🔄 **Conversation Continuity**\n- Seamless multi-turn conversations across different modes\n- Automatic context preservation between tool calls\n- Smart file deduplication - never re-read the same files\n- Thread-based memory system for long-running tasks\n\n### 🤖 **Smart Model Selection**\n- **Auto mode** - Intelligent model selection based on task complexity\n- Support for multiple providers: OpenAI, Anthropic, Google, OpenRouter\n- Model restrictions via environment variables for cost control\n- Thinking depth control: minimal (0.5%), low (8%), medium (33%), high (67%), max (100%)\n\n### 📁 **Intelligent File Handling**\n- **embedded** - Full file con…","publisher":null,"homepage":"https://github.com/david-strejc/sage-mcp","repository":"https://github.com/david-strejc/sage-mcp","version":"0.2.1","license":"MIT","protocols":["mcp"],"tags":["mcp","model-context-protocol","ai-assistant","claude","openai","anthropic","gemini"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_david-strejc-sage-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"knowledge.reasoning","name":"Reasoning & Planning","confidence":1,"provenance":"derived"},{"slug":"code.review","name":"Code Review","confidence":0.836,"provenance":"derived"},{"slug":"code.debugging","name":"Debugging","confidence":0.802,"provenance":"derived"}],"categories":["code","knowledge"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_david-strejc-sage-mcp","registry":"pypi","observedAt":"2026-11-03T06:28:13.839Z","publishedAt":"2026-02-11T23:22:53.175007Z","latestVersion":"0.2.1"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_david-strejc-sage-mcp","url":"https://pypi.org/project/iflow-mcp_david-strejc-sage-mcp/","firstSeenAt":"2026-09-09T18:21:46.144Z","fetchedAt":"2026-11-03T06:26:32.459Z","normalizedAt":"2026-11-03T06:26:32.459Z"}]},"firstSeenAt":"2026-09-09T18:21:46.144Z","updatedAt":"2026-11-03T06:28:13.839Z"}