Model Context Protocol with Neo4j for managing context between large language models and external systems.
Fully local web research assistant using LLMs for generating queries, summarizing results, and writing reports.
Large Action Model framework for developing AI Web Agents to automate processes effectively.
Your AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research.
A Go implementation of the Model Context Protocol (MCP) for LLM applications.
A prompt management, versioning, testing, and evaluation inference server and UI toolkit, provider agnostic and OpenAI API compatible.
Build LangGraph agents with large numbers of tools - a Python library to enhance agent capabilities.
A seamless integration of ChatGPT, OpenRouter.ai, and local LLMs into Obsidian for smooth AI-assisted note-taking.
A flexible Python library and CLI tool for interacting with Model Context Protocol (MCP) servers using any LLM model.
