This framework provides a server-based architecture supporting Multiple-MCP (Multi-Channel Processing) servers to handle concurrent conversations, maintain context across sessions, and integrate external services via plugins. Developers can configure connectors for messaging platforms, define custom function calls, and scale instances using Docker or native hosts. It includes logging, error handling, and a modular pipeline to extend capabilities without altering core code.

Agentfy provides a modular architecture for constructing AI agents by combining LLMs, memory backends, and tool integrations into a cohesive runtime. Developers declare agent behavior using Python classes, register tools (REST APIs, databases, utilities), and choose memory stores (local, Redis, SQL). The framework orchestrates prompts, actions, tool calls, and context management to automate tasks. Built-in CLI and Docker support enable one-step deployment to cloud, edge, or desktop environments.

The Kurtosis AutoGPT Package is an AI Agent framework packaged as a Kurtosis module that delivers a fully configured AutoGPT environment with minimal effort. It provisions and wires up services such as PostgreSQL, Redis, and a vector store, then injects your API keys and agent scripts into the network. Using Docker and Kurtosis CLI, you can spin up isolated agent instances, view logs, adjust budgets, and manage network policies. This package removes infrastructure friction so teams can rapidly develop, test, and scale autonomous GPT-driven workflows in a reproducible manner.