mcp-cornell-resume
0
Cornell Resume is a Model Context Protocol server designed to automatically generate Cornell-style study notes from conversational context. It integrates with Notion, uses OpenAI for processing, and features semantic search with Pinecone for enhanced note management.
MCP: Cornell Resume
A Model Context Protocol (MCP) server that automatically generates Cornell-style study notes and summaries from conversational context, featuring RAG active recall question generation and Notion integration.
Features
- Generates real-time Cornell-style notes from client chat history
- Context-aware active recall question generation using vector similarity
- Semantic search integration with Pinecone for note retrieval
- Automatic Notion database synchronization with proper formatting
- Powered by OpenAI for text processing and question generation
Setup Guide
- Requires Python 3.13+, uv, and accounts on OpenAI and Pinecone
- Clone the repository and install dependencies in a virtual environment
- Configure environment with API keys and set up Pinecone and Notion integration
Usage
- Configure MCP-compatible application to use server
- Use 'save_resume_to_notion' tool to summarize chat and send to Notion
Available Tools
save_resume_to_notion: Summarizes chat conversation and returns Notion page ID
How It Works
- Processes input text from MCP client
- Creates embeddings with OpenAI
- Retrieves context with Pinecone
- Generates Cornell summary using related notes
- Stores new note in Pinecone and saves to Notion