Generate code or get programming guidance by providing tasks, language hints, and context. This tool helps developers write, debug, and understand code through AI assistance.
Retrieve curated code examples with explanations for specific topics and libraries. Specify the programming language to find relevant snippets for your development tasks.
Discover and analyze code patterns across programming languages within a knowledge graph. Filter results by language or pattern name to enhance code understanding and retrieval.
Discover code examples in Bear notes by specifying a programming language and topic. Extract code blocks from relevant notes to solve coding challenges or learn new concepts efficiently.
Modify Jupyter notebook cell source code by specifying the notebook path, cell identifier, and new content to update programming logic or documentation.
Enables AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.
MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to:
Submit and validate constraint models
Set model parameters
Solve constraint satisfaction and optimization problems
Retrieve and analyze solution
A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.