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DevContext is a cutting-edge Model Context Protocol (MCP) server designed to provide developers with continuous, project-centric context awareness. Unlike traditional context systems, DevContext continuously learns from and adapts to your development patterns and delivers highly relevant context providing a deeper understanding of your codebase.
DevContext is a cutting-edge Model Context Protocol (MCP) server designed to provide developers with continuous, project-centric context awareness. Unlike traditional context systems, DevContext continuously learns from and adapts to your development patterns and delivers highly relevant context providing a deeper understanding of your codebase.
QueryPilot is an advanced document intelligence platform that combines Large Language Models (LLMs) with vector embeddings to enable natural language querying of your documents. The application processes various file formats (PDFs, DOCXs, TXT files, and images), extracting and embedding content for semantic search and AI-powered analysis.
The llm_to_mcp_integration_engine is a communication layer designed to enhance the reliability of interactions between LLMs and tools (like MCP servers or functions).
A powerful Custom Tool that enables AI agents to autonomously execute GraphQL queries and mutations. This package allows AI agents to intelligently interact with GraphQL APIs, making decisions about when and how to fetch or modify data through GraphQL endpoints without explicit human intervention.
This repo demonstrates how to build interactive AI agent interfaces using Chainlit. It combines LangChain, OpenAI/Gemini, and custom tools to enable seamless conversations and fast deployment of agent workflows with Python.