vibeDazi MCP server for team-shared vibe logs with git context
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# vibeDazi MCP Server  [中文文档 README_CH.md](README_CH.md) Team-shared MCP logging with git user/branch/diffs and prompt context. ## Install ```bash ./install-vibedazi.sh ``` ## Run ```bash vibedazi-mcp ``` ## VSCode MCP Create `.vscode/mcp.json`: ```json { "servers": { "vibedazi": { "type": "stdio", "command": "vibedazi-mcp" } } } ``` ## Cursor MCP Create or update `~/.cursor/mcp.json`: ```json { "mcpServers": { "vibedazi": { "type": "stdio", "command": "/absolute/path/to/your/.venv-vibedazi/bin/vibedazi-mcp" } } } ``` Tip: running `./install-vibedazi.sh` will create the venv, install the package, and write this file for you using the correct absolute path. ## Project policy The installer writes a root-level `rule.md` with the policy. Load it into your project prompt (or leave it for teammates to read). ## AI Squash Merge tool This MCP exposes a helper to attribute AI work without cluttering history. - Tool: `ai_squash_merge` - Flow: creates `ai/<timestamp>-<hint>` branch, commits current changes with AI author, switches back, and `git merge --squash` into your base branch. Optionally deletes the AI branch. When To Call - After you’ve finished an AI-assisted change and validated it (tests/build pass). - Call it right before your final `log_round` (so `log_round` remains last). - Goal: attribute the work to the AI author without interrupting your development flow. How To Call - In Cursor/VSCode MCP Tools: run `vibedazi.ai_squash_merge` with the params below. - Or from Python while your venv is active. Parameters (common) - `branch_hint`: optional suffix in branch name - `model_name`: label like `GPT-5`, `Claude`, `o3` (no default; pass explicitly to attribute the right model) - `author_name`, `author_email`: optional overrides for AI identity (if omitted, inferred from model_name) - `base_branch`: target branch (defaults t…
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