kaggle-mcp
by dexhunter
README.md
# kaggle-mcp MCP server
A MCP server for Kaggle Apis
## Components
### Tools
The server implements one tool:
- add-note: Adds a new note to the server
- Takes "name" and "content" as required string arguments
- Updates server state and notifies clients of resource changes
## Configuration
Ensure that you have downloaded your Kaggle credentials
(`kaggle.json`) and placed it in the `~/.kaggle/` directory (this is the default
location where the Kaggle API looks for your credentials)
Otherwise you can add the env `KAGGLE_USERNAME` and `KAGGLE_KEY` to the mcp config
## Quickstart
### Install
#### Claude Desktop
On MacOS: `~/Library/Application\ Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`
<details>
<summary>Development/Unpublished Servers Configuration</summary>
```
"mcpServers": {
"kaggle-mcp": {
"command": "uv",
"args": [
"--directory",
"/Users/{username}/Work/kaggle-mcp",
"run",
"kaggle-mcp"
]
}
}
```
</details>
<details>
<summary>Published Servers Configuration</summary>
```
"mcpServers": {
"kaggle-mcp": {
"command": "uvx",
"args": [
"kaggle-mcp"
]
}
}
```
</details>
## Development
### Building and Publishing
To prepare the package for distribution:
1. Sync dependencies and update lockfile:
```bash
uv sync
```
2. Build package distributions:
```bash
uv build
```
This will create source and wheel distributions in the `dist/` directory.
3. Publish to PyPI:
```bash
uv publish
```
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token: `--token` or `UV_PUBLISH_TOKEN`
- Or username/password: `--username`/`UV_PUBLISH_USERNAME` and `--password`/`UV_PUBLISH_PASSWORD`
### Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging
experience, we strongly recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector).
You can launch the MCP Inspector via [`npm`](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:
```bash
npx @modelcontextprotocol/inspector uv --directory /Users/{username}/Work/kaggle-mcp run kaggle-mcp
```
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.TDQS
B3.1/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no possibility of confusion between tools, so disambiguation is perfect.
Naming Consistency5/5
The single tool follows a consistent verb_noun pattern (prepare_kaggle_dataset), so naming is perfectly consistent.
Tool Count1/5
Only one tool for a server named 'kaggle-mcp' is far too few; a typical Kaggle interaction requires multiple operations beyond just downloading.
Completeness1/5
The single tool covers only dataset download/extraction, missing essential CRUD operations, search, and listing, making the surface severely incomplete.
Maintenance
ActivityInactive
ResponsivenessUnresponsive