Proposal
Add a new example notebook showing how to use the XPOZ MCP server (https://xpoz.ai) with the Gemini API for cross-platform social media intelligence.
What it teaches
- Connecting to a remote MCP server via HTTP (JSON-RPC protocol)
- Fetching social data from Twitter, Reddit, and Instagram through a single MCP interface
- Using Gemini to produce structured sentiment analysis from ~800 social posts
Why it's useful
MCP (Model Context Protocol) is becoming a standard way for AI models to access external tools and data. This cookbook demonstrates a practical, real-world use case: analyzing social media sentiment across multiple platforms using a single MCP server, combined with Gemini's analysis capabilities.
Technical details
- Uses direct HTTP JSON-RPC (no MCP SDK dependency)
- Handles both JSON and SSE response formats
- Parses XPOZ's compact tabular response format
- Follows Google cookbook style guide (copyright header, Colab badge, @param dropdown, userdata for keys)
- Tested end-to-end in Google Colab
Proposed location
examples/Social_media_intelligence_with_XPOZ_MCP.ipynb
Proposal
Add a new example notebook showing how to use the XPOZ MCP server (https://xpoz.ai) with the Gemini API for cross-platform social media intelligence.
What it teaches
Why it's useful
MCP (Model Context Protocol) is becoming a standard way for AI models to access external tools and data. This cookbook demonstrates a practical, real-world use case: analyzing social media sentiment across multiple platforms using a single MCP server, combined with Gemini's analysis capabilities.
Technical details
Proposed location
examples/Social_media_intelligence_with_XPOZ_MCP.ipynb