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Install and run MCP tool servers quickly inside Dataiku code environments.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "my-portfolio-mcp" yet — see the docs or source repo.
Explain how to install and configure my-portfolio-mcp in a Dataiku code environment, including dependencies, startup commands, and basic verification steps.
A practical setup guide with install commands, configuration steps, startup flow, and a verification checklist.
Give me an example showing how to call and run an MCP tool through my-portfolio-mcp in a Dataiku environment, and explain the input and output structure.
A usage example showing the execution flow, request parameter format, and sample returned results.
If my-portfolio-mcp fails to start after installation in Dataiku, list common causes, troubleshooting steps, and recommended fixes.
A troubleshooting checklist covering environment dependencies, path configuration, permission issues, and log inspection advice.
Connect to Jupyter via MCP to run code and explore data interactively.
Build and manage MCP servers and clients quickly with Python.
Turn Markdown files into local MCP servers to define and run tools.
Deploy a production-ready MCP server with demo tools and interactive testing UI.
Query an AI project portfolio, search by tech, and get project details.
Use zero-config MCP servers for web search and AI-driven Hexo blog management.