About this project
DawnMCP is a fully local, privacy-first MCP (Model Context Protocol) server that gives AI coding assistants deep understanding of a codebase — without sending any code to the cloud. WHAT IT DOES DawnMCP indexes an entire repository locally and answers natural-language questions with grounded, file-and-line-cited responses — not guesses. It maintains persistent semantic memory across sessions, so project decisions and context are remembered instead of lost between conversations. And it goes beyond Q&A: DawnMCP's AI agents can plan tasks, review code, and help debug issues by reasoning over the actual indexed codebase. WHO IT'S FOR Teams and researchers working with proprietary or unpublished code — students on unpublished research, companies with sensitive IP, or anyone who currently can't use cloud-based AI coding tools at all. DawnMCP gives them a real, capable alternative instead of a memoryless local chatbot. WHAT MAKES IT SPECIAL - Zero cloud API calls: every model call runs through a local Ollama instance (qwen2.5-coder for reasoning, nomic-embed-text for embeddings), with ChromaDB for local vector storage - No API keys, no per-token costs — fully offline-capable - Built on an open standard (MCP), not a closed plugin system — works with any MCP-compatible client - Deployable to NitroCloud when you do want a shareable endpoint, while all inference stays local Built on the NitroStack framework, DawnMCP also surfaced and fixed a real dependency-injection timing bug in the underlying framework — where config-dependent providers could silently fail to initialize under HTTP/SSE transport — demonstrating genuine engineering depth beyond a surface-level demo.
Enterprise AI & Workplace Automation track
Develop AI agents and automation tools that improve productivity, streamline workflows, and enhance business operations.