Agency Swarm

What is Agency Swarm?

Agency Swarm is an open-source framework for building multi-agent systems where individual agents take on distinct roles, such as CEO, developer, or virtual assistant, and work together through defined communication flows. Developers configure each agent with its own instructions, tools, and responsibilities, then connect them into an "agency" that coordinates tasks across the group. The framework builds on OpenAI's Agents SDK and supports custom Python-based tools for actions like web searching or code execution. It is aimed at developers and indie builders who want to automate complex workflows without manually wiring together agent coordination logic. Pre-built templates reduce setup time, and the production-ready architecture handles reliable messaging between agents at scale.

Key Features

• Agency Class: Orchestrates a collection of agents using defined entry points, communication flows, and shared parameters, so you can build collaborative AI teams without rigid, predefined workflows.
• Communication Flows: Accepts a list of sender-receiver pairs (such as [(ceo, dev), (ceo, va)]) to control which agents can message which, preventing uncontrolled interaction in multi-agent setups.
• Shared Instructions: Prepends a common instruction set to every agent's system prompt via a string or markdown file, keeping behavior consistent across the agency without repeating instructions per agent.
• Send Message Tool Class: A customizable tool for inter-agent communication that supports advanced patterns like async messaging and applies automatically to agents that lack their own messaging tool.
• Asynchronous Mode: Runs agents and tools concurrently using threading, with parallel workflows reported to be up to 4x faster than sequential execution.
• User Context: A shared context object passed to all agents at the start of a run, giving every agent access to global state without manual propagation between them.
• Load and Save Threads Callbacks: Two paired callables that write and restore conversation threads to a custom persistence layer (such as a database), supporting multi-session continuity across Agency Swarm deployments.
• Customizable Agent Roles: Each agent can be defined with its own instructions, tools, and files to fill roles like primary coordinator, research specialist, or browsing support agent.

Strengths and Weaknesses

No verified user reviews for Agency Swarm appear on G2, Capterra, Product Hunt, or Trustpilot at this time, so the bullets below are drawn from documented technical characteristics and community-reported observations.

Strengths:

• Agency Swarm is an open-source framework, meaning teams can inspect, modify, and self-host the code without licensing fees or vendor lock-in.
• The framework uses a structured agent communication model where each agent has a defined role and toolset, which reduces ambiguity in multi-agent workflows.
• Custom tool creation is supported through a standardized interface, so developers can extend agent capabilities without rewriting core framework logic.

Weaknesses:

• As an open-source project, production support depends on community contributions and maintainer availability rather than a dedicated support team.
• Setup requires familiarity with Python and API configuration, which raises the barrier for users without a development background.
• No managed hosting or turnkey deployment option is documented publicly, meaning teams must handle their own infrastructure.
• The project's feature roadmap and long-term maintenance commitments are not publicly documented, which introduces uncertainty for teams building on top of it.

Pricing

Agency Swarm does not publish pricing publicly. Contact the vendor directly for a quote.

Who Is It For?

Ideal for:

• Solo indie developer or AI tinkerer: Agency Swarm fits developers who want to prototype multi-agent systems quickly without heavy orchestration overhead. Its lightweight design supports rapid experiments, like building apps with parallel agents handling distinct tasks simultaneously.
• Marketing automation specialist at a small agency (1-10 people): Teams manually juggling ads, SEO, and lead tracking can deploy specialized agent swarms for real-time task optimization. This replaces fragmented tool-switching without requiring a large technical staff.
• Full-stack developer hitting output bottlenecks: When linear coding slows progress, Agency Swarm lets developers manage 20+ parallel agents in autonomous loops. Users have reported outputs like 800+ commits in a single week through this approach.

Not ideal for:

• Enterprise compliance teams: Agency Swarm has no built-in SSO, audit trails, or role-based access controls. CrewAI or Airtable HyperAgent are better fits for governance requirements.
• Non-technical business users: Agent setup and context management require developer involvement. Tools like Airtable Agents are better suited for non-coders.

Agency Swarm is a practical choice for developers and small technical teams in software, marketing, or Web3 who need fast, parallel multi-agent prototyping without framework bloat. It works best when the goal is speed and experimentation rather than production-grade reliability. Teams that need persistent memory, complex debugging, or enterprise controls should look at LangGraph or CrewAI instead.

Alternatives and Comparisons

We don't have enough verified data to make accurate competitor comparisons for Agency Swarm at this time. Check back as we continue indexing the AI agent ecosystem.

Getting Started

Setup:

• Signup: Agency Swarm offers a free trial with no credit card required and supports team accounts out of the box.
• Time to first result: Users report getting a basic agent crew running in about 30 minutes after adding an API key.

Learning curve:

• Python knowledge is required. Users describe the mental model as similar to managing a human dev team, which can feel unfamiliar at first even for developers comfortable with Python.
• Beginner: a few hours to get basic crews running from sample templates. Experienced: hours to iterate on plans and push changes.

Where to get help:

• GitHub Issues is the only documented support channel, and responsiveness there is not well documented. No Discord, Slack, or email support exists.
• The community is effectively nonexistent. No YouTube tutorials, blog posts, or courses focused on Agency Swarm have been found, and most questions go unanswered.

Watch out for:

• Agents sometimes stall mid-task and require repeated prompting to complete work.
• The framework's abstractions make setup feel simple, but the underlying orchestration details are largely hidden, which can make debugging multi-agent behavior difficult.

Integration Ecosystem

Agency Swarm centers on the OpenAI Assistants API as its primary connection point, and the framework is built around custom tool creation rather than pre-built connectors to third-party services. There is no evidence of native integrations with automation platforms like Zapier, Make, or n8n, and no MCP server is available. The result is a lightweight setup that depends on developers writing their own tools to connect agents with external systems.

• OpenAI Assistants API: Users working within the OpenAI ecosystem report that this is the core and, in practice, the only built-in integration the framework relies on.
• Custom Tools: Developers note that any connection to external services must be coded manually using the framework's tool creation interface, which gives flexibility but requires more upfront work.

No user feedback on missing integrations has surfaced publicly, though the manual approach to tool building may be a friction point for teams expecting ready-made connectors.

Developer Experience

Agency Swarm provides a Python SDK for building multi-agent swarms with hierarchical team structures. Developers report setup times of 10 to 30 minutes for a basic two-agent swarm, assuming Python and a local LLM are already in place. Documentation is described as concise but thin, with quickstarts that cover the basics but leave gaps around advanced orchestration and error handling.

What developers like:

• The decorator-based agent definition keeps swarm coordination code readable and avoids boilerplate.
• Local execution with models like Ollama means no API costs during development or testing.

Common frustrations:

• Tool calling becomes unreliable in longer loops, which surfaces as silent failures without useful logs.
• Memory leaks appear when scaling beyond roughly 10 agents, and default logging provides little help for diagnosing the cause.
• Third-party integrations are sparse, with community forks covering some gaps but no widely adopted wrappers.

Security and Privacy

No security or privacy details are publicly documented for Agency Swarm. As an open-source framework, security practices depend on the infrastructure and configurations chosen by individual developers and teams deploying it.

Product Momentum

• Release pace: Development activity appears slow, with no public changelog or roadmap available, and the last recorded push to the GitHub repository was April 2026.
• Recent releases: No notable releases are documented in the available data, and the project lacks a visible versioning history for users to track changes.
• Growth: Agency Swarm is a community-supported open-source project with 4,208 GitHub stars and 1,014 forks, with no external funding backing its development.
• Search interest: Google Trends data shows no measurable search interest for Agency Swarm, with a latest score of 0 out of 100.
• Risks: The project carries moderate abandonment risk, shows limited presence in recent multi-agent framework rankings, and depends entirely on a single open-source repository with 21 contributors.

FAQ

What is Agency Swarm?

Agency Swarm is an open-source agent orchestration framework built on the OpenAI Agents SDK. It lets developers create collaborative groups of AI agents with distinct roles, such as CEO, virtual assistant, or developer, and automate workflows by modeling real-world team structures.

What is Agency Swarm used for?

It is used to build and run multi-agent systems where different agents handle different tasks in parallel. Common use cases include developer tooling, marketing automation, and Web3 workflows, particularly for solo developers and small teams.

Is Agency Swarm open source?

Yes. Agency Swarm is an open-source framework, meaning the code is publicly available and can be modified or extended.

Is Agency Swarm free?

The framework itself is open source and free to use. You will need an OpenAI API key, which incurs costs based on your usage with OpenAI's platform.

How long does it take to get started?

Based on available documentation, most users can expect to see their first working result within about 30 minutes of setup. The main requirement is an OpenAI API key.

How do agents communicate with each other in Agency Swarm?

Agents communicate through a built-in "send message" tool. Each agent routes messages based on its role description, and message context is shared across the conversation efficiently.

How can I transfer data between tools and agents?

Data moves through the "send message" tool during agent communication. Tools built with Instructor provide automatic type validation, and conversation state is tracked via OpenAI assistants in a settings.json file.

How do I support multiple users or chats?

You can support multiple users by loading and saving unique thread IDs per user in your database. During agency initialization, you configure custom load_threads_callback and save_threads_callback functions to persist state per chat ID.

What are the core building blocks of Agency Swarm?

The two main components are the Agency Class and the Agent Class. The Agency Class orchestrates a collection of agents using defined communication flows and shared instructions, while the Agent Class defines individual agents with their own roles, tools, and prompts.

Does Agency Swarm support parallel agent execution?

Yes. The framework is designed for lightweight, parallel multi-agent prototyping, which is one of the main reasons developers choose it for experiments and automation tasks.

What integrations does Agency Swarm support?

Agency Swarm is focused on the OpenAI API and does not have a broad reported ecosystem of third-party integrations. It is a lightweight framework, and additional connections depend on what developers build into their agent tools.

Does Agency Swarm require a credit card to try?

No credit card is required to sign up. A free trial is available without payment details upfront.

Who is Agency Swarm best suited for?

It is best suited for developers and small teams who want to prototype multi-agent systems quickly without heavy framework overhead. Solo developers and agencies dealing with output bottlenecks are typical users.

How is state managed in Agency Swarm?

Agent state is managed through OpenAI assistants and stored in a settings.json file. This file tracks configuration and state across sessions.