| Name | vibegit-mcp JSON |
| Version |
0.1.5
JSON |
| download |
| home_page | None |
| Summary | VibeGit MCP server for AI conversation logging and analysis |
| upload_time | 2025-09-13 13:29:55 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | MIT |
| keywords |
mcp
ai
conversation
logging
assistant
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# VibeGit MCP Server
A Model Context Protocol (MCP) server for logging and analyzing AI assistant conversations.
## Prerequisites
You need only two steps to get started:
### Step 1: Installation
```bash
pip install vibegit-mcp
```
### Step 2: Configuration
Once installed, you can configure the MCP configuration file to enable the VibeGit MCP server. Assuming you are using VSCode, you can add a `mcp.json` file in the `.vscode/` directory of your project with the following content:
```json
{
"servers": {
"vibegit": {
"type": "stdio",
"command": "vibegit-mcp"
}
}
}
```
## Usage
After configuring the MCP server, you can start your AI Coding Agent in VSCode. The VibeGit MCP server will automatically log all conversation rounds to the `.vibe/` directory in your project root.
## Features
- Log complete conversation rounds between users and AI assistants
- Track file operations and tool usage
All the logs and data are stored in the `.vibe/` directory under the project root. The directory structure is as follows:
```
.vibe/
├── rounds/
│ ├── 2023-03/
│ │ ├── round-1.json
│ │ ├── round-2.json
│ ├── 2023-04/
│ │ ├── round-3.json
│ │ ├── round-4.json
├── index.jsonl
├── sessions/
│ ├── session-1.json
│ ├── session-2.json
```
Each `round-*.json` file contains detailed information about a single conversation round, including user inputs, AI responses, and any file operations and tool usage performed. The `index.jsonl` file provides a quick reference to all rounds, and the `sessions/` directory contains session metadata. Each session contains the consecutive rounds of conversations.
## Building and Publishing (For Maintainers)
This package uses modern Python packaging with `pyproject.toml`.
#### Prerequisites
Install build tools:
```bash
pip install build twine
```
Set up PyPI credentials in `~/.pypirc`:
```ini
[distutils]
index-servers =
pypi
testpypi
[pypi]
repository = https://upload.pypi.org/legacy/
username = __token__
password = # your PyPI API token (pypi-...)
[testpypi]
repository = https://test.pypi.org/legacy/
username = __token__
password = # your TestPyPI API token (pypi-...)
```
#### Release Process
1. **Update version** in `pyproject.toml`:
```toml
version = "x.y.z" # Increment as needed
```
2. **Clean previous builds**:
```bash
rm -rf dist/ build/ *.egg-info
```
3. **Build the package**:
```bash
python -m build
```
4. **Test upload to TestPyPI** (optional but recommended):
```bash
python -m twine upload --repository testpypi dist/*
```
5. **Test installation from TestPyPI**:
```bash
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ vibegit-mcp==x.y.z
```
6. **Upload to PyPI**:
```bash
python -m twine upload dist/*
```
#### Notes
- Always test with TestPyPI first before publishing to PyPI
- Make sure to increment the version number for each release
- The package uses `pyproject.toml` for modern Python packaging standards
- Clean the `dist/` directory before building new releases
## License
MIT License
Raw data
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"description": "# VibeGit MCP Server\r\n\r\nA Model Context Protocol (MCP) server for logging and analyzing AI assistant conversations.\r\n\r\n## Prerequisites\r\n\r\nYou need only two steps to get started:\r\n\r\n### Step 1: Installation\r\n\r\n```bash\r\npip install vibegit-mcp\r\n```\r\n\r\n### Step 2: Configuration\r\n\r\nOnce installed, you can configure the MCP configuration file to enable the VibeGit MCP server. Assuming you are using VSCode, you can add a `mcp.json` file in the `.vscode/` directory of your project with the following content:\r\n\r\n```json\r\n{\r\n \"servers\": {\r\n \"vibegit\": {\r\n \"type\": \"stdio\",\r\n \"command\": \"vibegit-mcp\"\r\n }\r\n }\r\n}\r\n```\r\n\r\n## Usage\r\n\r\nAfter configuring the MCP server, you can start your AI Coding Agent in VSCode. The VibeGit MCP server will automatically log all conversation rounds to the `.vibe/` directory in your project root.\r\n\r\n## Features\r\n\r\n- Log complete conversation rounds between users and AI assistants\r\n- Track file operations and tool usage\r\n\r\nAll the logs and data are stored in the `.vibe/` directory under the project root. The directory structure is as follows:\r\n\r\n```\r\n.vibe/\r\n\u251c\u2500\u2500 rounds/\r\n\u2502 \u251c\u2500\u2500 2023-03/\r\n\u2502 \u2502 \u251c\u2500\u2500 round-1.json\r\n\u2502 \u2502 \u251c\u2500\u2500 round-2.json\r\n\u2502 \u251c\u2500\u2500 2023-04/\r\n\u2502 \u2502 \u251c\u2500\u2500 round-3.json\r\n\u2502 \u2502 \u251c\u2500\u2500 round-4.json\r\n\u251c\u2500\u2500 index.jsonl\r\n\u251c\u2500\u2500 sessions/\r\n\u2502 \u251c\u2500\u2500 session-1.json\r\n\u2502 \u251c\u2500\u2500 session-2.json\r\n```\r\nEach `round-*.json` file contains detailed information about a single conversation round, including user inputs, AI responses, and any file operations and tool usage performed. The `index.jsonl` file provides a quick reference to all rounds, and the `sessions/` directory contains session metadata. Each session contains the consecutive rounds of conversations.\r\n\r\n## Building and Publishing (For Maintainers)\r\n\r\nThis package uses modern Python packaging with `pyproject.toml`.\r\n\r\n#### Prerequisites\r\n\r\nInstall build tools:\r\n```bash\r\npip install build twine\r\n```\r\n\r\nSet up PyPI credentials in `~/.pypirc`:\r\n```ini\r\n[distutils]\r\nindex-servers =\r\n pypi\r\n testpypi\r\n\r\n[pypi]\r\nrepository = https://upload.pypi.org/legacy/\r\nusername = __token__\r\npassword = # your PyPI API token (pypi-...)\r\n\r\n[testpypi]\r\nrepository = https://test.pypi.org/legacy/\r\nusername = __token__\r\npassword = # your TestPyPI API token (pypi-...)\r\n```\r\n\r\n#### Release Process\r\n\r\n1. **Update version** in `pyproject.toml`:\r\n ```toml\r\n version = \"x.y.z\" # Increment as needed\r\n ```\r\n\r\n2. **Clean previous builds**:\r\n ```bash\r\n rm -rf dist/ build/ *.egg-info\r\n ```\r\n\r\n3. **Build the package**:\r\n ```bash\r\n python -m build\r\n ```\r\n\r\n4. **Test upload to TestPyPI** (optional but recommended):\r\n ```bash\r\n python -m twine upload --repository testpypi dist/*\r\n ```\r\n\r\n5. **Test installation from TestPyPI**:\r\n ```bash\r\n pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ vibegit-mcp==x.y.z\r\n ```\r\n\r\n6. **Upload to PyPI**:\r\n ```bash\r\n python -m twine upload dist/*\r\n ```\r\n\r\n#### Notes\r\n\r\n- Always test with TestPyPI first before publishing to PyPI\r\n- Make sure to increment the version number for each release\r\n- The package uses `pyproject.toml` for modern Python packaging standards\r\n- Clean the `dist/` directory before building new releases\r\n\r\n## License\r\n\r\nMIT License\r\n",
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