What data formats does Flashcardgenerator accept?
It accepts JSON and CSV input. The `convert_csv_to_json` tool transforms CSV content into the required JSON flashcard format.
@Moonzhang
Basic information
A FastMCP-based MCP server for converting JSON-formatted Markdown content into interactive flashcard pages.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"FlashcardGenerator": {
"command": "uv",
"args": [
"--directory",
"/path/to/FlashCardMCP",
"run",
"/server.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Flashcardgenerator is an MCP service built on FastMCP that converts JSON or CSV formatted Markdown content into interactive flashcard HTML pages. It also supports generating printable PDF flashcards (8‑card layout). The service is designed for learning, teaching, knowledge management, and any scenario where users want to create digital flashcard sets.
Install dependencies with uv sync or pip install -e ., then run the server with python server.py. The MCP server uses the STDIO transport protocol and is compatible with MCP clients like Claude Desktop. The server exposes resources and tools that can be invoked through the MCP protocol.
It accepts JSON and CSV input. The `convert_csv_to_json` tool transforms CSV content into the required JSON flashcard format.
Python with FastMCP installed. Dependencies are managed via `uv sync` or `pip install -e .`.
HTML flashcard content is returned as a string. For PDF export, you must specify an `output_path` directory where the PDF file will be saved.
The server uses STDIO transport by default, compatible with MCP clients such as Claude Desktop.
The Listen template’s speech functionality uses the Web Speech API, which may have variable quality across browsers. The project is under active development; more templates and an online demo are planned.

Handl speaks the Model Context Protocol. Your whole billing operation — projects, invoices, clients, reports, approvals — as tools any AI assistant can call, inside your autonomy rules.

Model Context Protocol Servers
不止于 CSS
A curated list of references for MLOps
Open-source MCP to use Blender with any LLM
Comments