Open-Source AI Agent Frameworks

Multi-Agent Shogun runs and coordinates separate AI coding assistants on your computer or a Linux server. It's for developers dividing implementation and research across parallel tasks. Coordination happens locally, but Claude Code’s standard cloud connection sends prompts and model outputs over the network to their model provider; other agents use their chosen CLI's model access and authentication.

OpenCrust is a self-hosted AI assistant platform for people who want agents to handle tasks through their messaging apps. Named agents can pass work to one another and retain conversation memory between sessions.

TradingAgents is an open-source Python framework for researchers and developers studying AI trading decisions. It assigns market analysis and risk assessment to separate LLM agents, then combines their findings into a proposed trade for a simulated exchange.

LazyLLM is a Python framework for developers building applications with multiple AI agents. It brings application workflows, model training and evaluation together so teams can refine a prototype using task-specific data.

OASIS is a social media simulator for researchers studying how information spreads, groups polarize, and users follow the crowd. It uses LLM agents as simulated participants in Twitter and Reddit environments.

Rig is a Rust library for developers building AI agents and LLM applications. It provides a shared interface across model providers and vector stores for applications that need to work with different backends.

Forge Orchestrator coordinates Claude Code, Codex CLI and Gemini CLI working on the same repository, so they can share decisions and avoid conflicting edits. It's built for internal use at NXTG; outside use isn't supported, there's no SLA, and interfaces may change without notice.

Rivet AgentOS is a runtime for developers building applications where AI agents need a working environment for code and tools. It runs inside an existing backend process, with WebAssembly isolation instead of a separate virtual machine for each agent.

txtai is a Python framework for developers building search, chat with their data, and AI agents on their own hardware. It combines a searchable knowledge store with model workflows, so applications can retrieve context and act on it.

LlamaIndex is a Python framework for developers building AI agents and applications that answer questions using their own data. It provides the connections and retrieval tools needed to give a language model relevant context from documents and other sources.

Pi Subagents is an extension for developers who want to divide coding work among specialized AI agents in pi. Agents run in separate sessions, so you can assign distinct roles and follow their progress individually.

MASFactory is a Python framework for developers building workflows in which several AI agents collaborate. It combines natural-language design, code authoring and visual editing so teams can define the work and inspect how agents carry it out.

OpenRath is a Python runtime for developers building multi-agent workflows that need an inspectable record of their work. It keeps context and evidence together so engineering and research teams can trace how a result was produced.

OpenShell is a self-hosted runtime for teams that need autonomous AI agents to work with files and APIs under explicit access limits. It runs agents in isolated sandboxes and enforces policies at the kernel level.

OpenRig coordinates coding agents for developers working on projects that last weeks or months. You talk to a lead agent, which delegates to specialists and brings back results or decisions that need your attention.

Haystack is a Python framework for developers building AI agents, document search and applications that answer questions using their own data. Its pipelines give teams control over the information a model receives and the steps that produce an answer.

IntentKit is a self-hosted AI agent framework for developers who need several agents to share work and carry out recurring tasks. It runs as a server application, with chat channels and APIs for interacting with the agents.

Sandcastle is a TypeScript library for developers building automated coding workflows in scripts, CI pipelines, or custom tools. It coordinates sandboxed AI coding agents and manages where their Git changes land.

Chidori is an AI agent framework for developers building long-running workflows that need crash recovery or human approval. Agents use ordinary async TypeScript, with saved runs that developers can revisit for debugging and testing.

Agno is a framework and runtime for developers building customer-facing or internal AI agents. It combines agent development, service hosting and a web interface for managing runs on infrastructure you control.

Pipecat is an open-source Python framework for developers who want to run voice and video agent applications locally or on their own servers. It hosts the conversation pipeline, while speech and model processing depend on the services you choose. Integrations such as Soniox, OpenAI and Cartesia send the relevant requests to those providers.

Ruflo is an AI agent framework for developers who want Claude Code and Codex to work as coordinated teams. It adds specialist roles and shared context for projects that involve coding, testing, architecture and documentation.

GitAgent is an AI agent framework for developers who want to version an agent's behavior and saved memory alongside its tools. Agent definitions live in a Git repository, where teams can review changes, fork agents and maintain different behaviors on separate branches.

Jido is an Elixir framework for developers who want to run cooperating agents inside their own application or self-hosted server. Its BEAM runtime handles agent state, tool execution and coordination. AI is optional: the core supplies the runtime, while jido_ai adds model integration separately.

OpenHarness SDK is a TypeScript toolkit for developers building coding assistants and other AI agents into their own applications. It gives the application control over conversation history, tool permissions and task delegation.

OGX, formerly Llama Stack, is an AI application server for developers building chat apps, document search and AI agents. It brings model access and the services those applications need into a server you can host yourself.

AX is a self-hosted AI agent orchestrator for teams running autonomous tasks on Kubernetes. It manages agents that retain state and need access to models, repositories and tools while they work.

GenericAgent runs tasks on your computer using cloud models to decide what to do. It's for people who want an AI agent to work across websites, files and desktop apps, then save successful workflows for reuse. Model calls require API keys and an internet connection, with requests going to the selected provider. It supports Claude, Gemini, Kimi and MiniMax.

Langflow is a visual builder for developers creating AI agents and applications that answer questions using connected data. It lets you assemble workflows visually and customize their components in Python.

nanobot is a self-hosted personal AI agent for people who want an assistant that can act on files and continue work across conversations. Its Python framework also suits developers building their own assistant integrations.

LiveKit Agents is a framework for developers building voice assistants, phone agents and applications that combine speech, video and text. Python and Node.js agents interact with users through LiveKit rooms connected to web, mobile or telephone clients.

DeerFlow is a self-hosted AI agent application for research, coding and content creation on your own infrastructure. It supports local models through Ollama and vLLM, including Qwen3, as well as hosted providers. With a cloud provider, model requests leave your server and may incur provider charges.

AI Legion is a self-hosted framework for developers who want several AI agents to work together on tasks. The program runs on your own machine through Node.js, while OpenAI's cloud models handle the language processing. It's open source under MIT.

MS Agent is an open source Python agent framework with a self-hosted web server for working on local projects. It's for developers building research assistants and coding workflows that continue across sessions. Code execution and project file work run locally; the default model integration uses ModelScope's API and requires an API key and internet access.