To run `markitdown-mcp` in Docker, build the Docker image using the provided Dockerfile:
```bash
docker build -t markitdown-mcp:latest .
```
And run it using:
```bash
docker run -it --rm markitdown-mcp:latest
```
This will be sufficient for remote URIs. To access local files, you need to mount the local directory into the container. For example, if you want to access files in `/home/user/data`, you can run:
```bash
docker run -it --rm -v /home/user/data:/workdir markitdown-mcp:latest
```
Once mounted, all files under data will be accessible under `/workdir` in the container. For example, if you have a file `example.txt` in `/home/user/data`, it will be accessible in the container at `/workdir/example.txt`.
[uv](https://docs.astral.sh/uv/) is an extremely fast alternative to [pip](https://pip.pypa.io/en/stable/) which allows running Python packages without installing them.
To debug the MCP server you can use the `mcpinspector` tool.
```bash
npx @modelcontextprotocol/inspector
```
You can then connect to the insepctor through the specified host and port (e.g., `http://localhost:5173/`).
If using STDIO:
* select `STDIO` as the transport type,
* input `markitdown-mcp` as the command, and
* click `Connect`
If using SSE:
* select `SSE` as the transport type,
* input `http://127.0.0.1:3001/sse` as the URL, and
* click `Connect`
Finally:
* click the `Tools` tab,
* click `List Tools`,
* click `convert_to_markdown`, and
* run the tool on any valid URI.
## Security Considerations
The server does not support authentication, and runs with the privileges if the user running it. For this reason, when running in SSE mode, it is recommended to run the server bound to `localhost` (default).
## Trademarks
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft