Skip to main content
Glama

Jupyter MCP Server

by datalayer
README.md2.01 kB
<!-- ~ Copyright (c) 2023-2024 Datalayer, Inc. ~ ~ BSD 3-Clause License --> # 📋 Jupyter MCP Server Prompt Templates Welcome to the Jupyter MCP Server Prompt Templates repository! This directory contains curated, community-driven prompt templates designed to help AI agents and users make the most of Jupyter MCP Server across different scenarios and use cases. ## 💡 How to Use Prompt Templates Templates are organized by use case, you can choose any of them. > [!TIP] > > Start with the `general/` template if you're new to Jupyter MCP Server. It provides foundational guidance applicable to most use cases. ### Example Usage ``` 1. Go to prompt/general/ 2. Read the README.md to understand the template's purpose 3. Copy the content from AGENT.md 4. Paste it as your system prompt(e.g. `CLAUDE.md` in Claude Code) 5. Start your session with enhanced context! ``` ## 🤝 Contributing Your Own Templates We love community contributions! If you've developed a great prompt template that works well with Jupyter MCP, here's how to share it: ### Step 1: Create a Template Directory Clone the repository and create a new folder with a clear, concise name representing the use case: ```bash git clone https://github.com/datalayer/jupyter-mcp-server.git cd jupyter-mcp-server/prompt mkdir your-use-case/ ``` ### Step 2: Create a README.md create a `README.md` file in the new folder and it should include the brief description of what this template is for. ### Step 3: Create the AGENT.md Create an `AGENT.md` file containing the actual system prompt for AI agents. ### Step 4: Add Resources (Optional) You can include additional files to enhance your template ### Step 5: Submit a Pull Request Create a pull request to let us know your Awesome Prompt Template! ## 🙏 Thank You Thank you for using and contributing to Jupyter MCP Server Prompt Templates! Your participation helps build a stronger community and makes AI-powered notebook workflows more accessible to everyone.

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/datalayer/jupyter-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server