MCP.so
Sign In

Mcp Cornell Resume

@johndezr

Repository

About Mcp Cornell Resume

A Model Context Protocol (MCP) server that automatically generates Cornell-style study notes and summaries from the conversational context, with RAG active recall question generation and Notion integration.

#notion#cornell#resume

Basic information

Category

Memory & Knowledge

Transports

stdio

Publisher

johndezr

Submitted by

John Galindez

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "resume_to_notion": {
      "command": "/path-to-uv/uv",
      "args": [
        "--directory",
        "/path-to-project/mcp-cornell-resume",
        "run",
        "main.py"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Mcp Cornell Resume?

An MCP server that generates Cornell-style study notes and active recall questions from conversational context. It uses RAG with Pinecone for context retrieval and automatically saves formatted summaries to a Notion database. Designed for users who want to turn chat history into structured study materials.

How to use Mcp Cornell Resume?

Set up by cloning the repository, installing dependencies with uv, and configuring environment variables (OpenAI, Pinecone, Notion API keys). Add the server to an MCP‑compatible client (e.g., Claude Desktop) using a JSON configuration pointing to uv run main.py. The tool save_resume_to_notion accepts a text string and returns a Notion page ID.

Key features of Mcp Cornell Resume

  • Real-time Cornell-style note generation from chat conversation history
  • Context-aware active recall question generation using vector similarity
  • Semantic search integration with Pinecone for relevant note retrieval
  • Automatic Notion database synchronization with proper block formatting
  • OpenAI-powered text processing and question generation

Use cases of Mcp Cornell Resume

  • Convert long chat conversations into structured Cornell notes for review
  • Generate active recall questions to test understanding of discussed topics
  • Maintain a searchable, organized knowledge base in Notion from chat sessions
  • Retrieve semantically related past notes while taking new ones

FAQ from Mcp Cornell Resume

What are the required dependencies and accounts?

Python 3.13+, the uv package manager, and accounts for OpenAI, Pinecone, and Notion. API keys must be stored in a .env file.

How does the data flow through the server?

The client sends chat text to save_resume_to_notion. OpenAI generates embeddings, Pinecone retrieves semantically similar notes, OpenAI creates a Cornell summary using that context, and the result is stored in both Pinecone and Notion. The Notion page ID is returned.

Where is my data stored?

Note content is saved to your Notion database with formatted blocks. Vector embeddings are stored in a Pinecone index for future context retrieval.

What are the current limitations?

The finite LLM context window (typically 8k–32k tokens) means very long conversations may lose information. Multiple integrations add latency, and Notion‑Pinecone sync is complex.

How are API keys handled?

All keys are stored in a .env file and never exposed in error messages. Input validation and access controls are applied according to Notion workspace permissions.

Comments

More Memory & Knowledge MCP servers

MCP server for Obsidian

MarkusPfundstein

MCP server that interacts with Obsidian via the Obsidian rest API community plugin

4.0K

Ultimate Google Docs & Drive MCP Server

a-bonus

The Ultimate Google Docs, Sheets, Drive, Gmail, & Google Calendar MCP Server. This MCP (primarily for use in Claude Desktop) gains full access to your google suite and lets claude do its thing.

605

🧠 Ultimate MCP Server

Dicklesworthstone

Comprehensive MCP server exposing dozens of capabilities to AI agents: multi-provider LLM delegation, browser automation, document processing, vector ops, and cognitive memory systems

154

Semantic Scholar MCP Server

YUZongmin

A FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks.

158

Rust Docs MCP Server

Govcraft

🦀 Prevents outdated Rust code suggestions from AI assistants. This MCP server fetches current crate docs, uses embeddings/LLMs, and provides accurate context via a tool call.

286