mdslides-mcp-server
An MCP server for generating HTML presentation slides from Markdown content using the mkslides library, enabling integration with tools like Claude in VSCode to create and manage presentations.
README
mdslides-mcp-server
An MCP (Model Context Protocol) server for generating HTML slides from Markdown content using the mkslides library.
What it Does
This server provides a simple interface to the mkslides command-line tool, allowing you to generate presentation slides directly from Markdown input via the Model Context Protocol. This enables integration with tools like Claude in VSCode to easily create and manage presentations.
Demo
Features
- Generate HTML slides from Markdown.
- Support for various mkslides configuration options (themes, highlight themes, Reveal.js options).
- Clean handling of temporary files.
- Containerized deployment option using Docker.
Installation
Prerequisites
- Python 3.12 or higher
- mkslides installed and available in your PATH.
- Model Context Protocol (MCP) client (e.g., Claude in VSCode).
- Docker (if using the Docker installation method).
Installation Methods
Using pip
- Clone the repository:
git clone https://github.com/your-repo/mdslides-mcp-server.git cd mdslides-mcp-server - Install using pip and uv (recommended):
Or using pip:uv syncpip install .
Using Docker
- Ensure Docker is installed and running.
- From the repository root, run the deployment script:
./deploy_mdslides_docker.sh
This script will build the Docker image (if not already built) and start a container instance named `mdslides-mcp-instance`. The server inside the container will be running and ready to accept connections via MCP. The script also handles creating the necessary output directory (`./mkslides_output`) on the host.
### Configuration in MCP Settings
To use the server with your MCP client (like Claude in VSCode), you need to add it to your MCP settings.
If you installed using pip, you can run the server directly:
```json
{
"mcpServers": {
"mdslides-mcp-local": {
"command": "python",
"args": ["src/mdslides_mcp_server/server.py"],
"disabled": false,
"autoApprove": []
}
}
}
If you are using the Docker deployment via the script:
Configure your MCP client to attach to the running container instance:
{
"mcpServers": {
"mdslides-mcp-local": {
"autoApprove": [],
"disabled": false,
"timeout": 60,
"command": "docker",
"args": [
"attach",
"mdslides-mcp-instance"
],
"transportType": "stdio"
}
}
}
Usage with Claude/VSCode
Once configured in your MCP settings, you can use the generate_slides tool directly within your Claude chat interface in VSCode.
Available Tool: generate_slides
Generates HTML presentation slides from Markdown input using mkslides and serves them via a local HTTP server.
Parameters:
markdown_content(string, required): Raw Markdown text for the slides.slides_theme(string, optional): Theme name for the slides (e.g.,black,white,league,beige,night,serif,simple,solarized,moon,dracula,sky,blood). Overrides the default.slides_highlight_theme(string, optional): Syntax highlighting theme for code blocks (any built-in theme fromhighlight.js).revealjs_options(object, optional): A dictionary containing Reveal.js config options to merge/override defaults.
Returns:
- (string): A URL (e.g.,
http://localhost:8080/latest/index.html) pointing to the generated HTML slides served by the MCP server's internal HTTP server. You can open this URL in your browser.
Example Usage:
<use_mcp_tool>
<server_name>mdslides-mcp-local</server_name>
<tool_name>generate_slides</tool_name>
<arguments>
{
"markdown_content": "# My Presentation\n\n---\n\n## Slide 2\n\n- Bullet 1\n- Bullet 2",
"slides_theme": "black",
"revealjs_options": {
"transition": "slide"
}
}
</arguments>
</use_mcp_tool>
This will generate the slides in the default output directory (./mkslides_output) using the 'black' theme and a 'slide' transition.
Development
Contributing
Contributions are welcome! Please follow standard GitHub practices: fork the repository, create a feature branch, and submit a pull request.
Running Tests
Currently, there is a placeholder test file (tests/test_server.py). To run tests, you would typically use a test runner like pytest:
pytest
Remember to add actual tests to tests/test_server.py.
Building from Source
Follow the pip installation steps above to set up your development environment.
License
This project is licensed under the MIT License - see the LICENSE file for details. (Note: A LICENSE file does not currently exist in the repository. You may want to create one.)
Acknowledgements
- mkslides for the core slide generation functionality.
- Model Context Protocol for enabling server integration.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.