Top 6 of 15 alternatives
Alternatives to AutoGen
Find a better fit. See what each alternative to AutoGen does better, where it falls short, and what it costs.
On this page
- 01
Agno
Python SDK plus self-hosted AgentOS runtime and hosted control plane for building and operating agents.
From FreeWhy it's on this listDebugs and fixes · YesBug fixing is a documented pattern: reproduce, patch, rerun the failing tests.Source ↗
Where it improves on AutoGen
Trade-offs against AutoGen
- −Open source · PartlyThe SDK and AgentOS runtime are open source and free at any scale, but the hosted control plane you pay for is not.Source ↗
- 02
AgentsKitVerified
Composable TypeScript packages for building AI agents, with swappable model, memory, tool and UI layers.
From FreeWhy it's on this listReviews code · YesA codeReviewer persona reads a diff hunk by hunk and returns a review verdict, and it is documented alongside the GitHub tool for commenting on pull requests.Source ↗
Where it improves on AutoGen
- +Agent permissions · YesTool calls are filtered by allow lists, deny lists and validators before execution, and individual tools can be marked as needing human confirmation before they run.Source ↗
- +Claude · YesA native Anthropic adapter covers the Claude model family with streaming and tool calls, and the delegation examples use a Claude model by default.Source ↗
Trade-offs against AutoGen
- −In a browser · PartlyThere is no hosted console for this library. It ships headless chat components for seven frameworks that you render inside your own web application and style yourself.Source ↗
- −Getting out · PartlyConversation state lives in storage you already own, such as a JSON file, SQLite or Postgres, and there are no vendor credits that could expire; no formal export tool is documented.Source ↗
- 03
Google Agent Development Kit (ADK)
Open-source framework for building, evaluating and deploying AI agents in Python, TypeScript, Go, Java or Kotlin.
From FreeWhy it's on this listShips it · YesDeployment is part of the framework: one command pushes an agent to Google Cloud, and the same agent can be containerised and run on infrastructure you control instead.Source ↗
Where it improves on AutoGen
- +Agent permissions · YesAutonomy is set per tool by the developer: a tool can be configured to pause and ask a human or a supervising system before it runs, though the vendor labels this confirmation feature experimental.Source ↗
- +Claude · YesClaude is supported in Python and Java, either through the registry wrapper on Google Cloud Agent Platform or directly against Anthropic with your own API key.Source ↗
Trade-offs against AutoGen
- −Writes code · PartlyADK does not write application code for you, but its Visual Builder inside the local web UI generates agent projects from a graphical design with an AI assistant, and the vendor marks that builder experimental and Python-only.Source ↗
- −In a browser · PartlyThe browser UI exists but you run it locally and the vendor bars it from production, so there is no hosted web application unless you deploy your own agent service.Source ↗
- 04
Pydantic AI
Open-source Python agent framework from the Pydantic team, with a typed agent loop and swappable models.
From FreeWhy it's on this listFor the reader who wants strict end-to-end typing and a lightweight, FastAPI-like developer experience while keeping the same multi-provider model flexibility AutoGen offered. Pydantic AI's own site and GitHub repo confirm MIT license, 19,400+ stars, typed outputs/dependency-injection/tools throughout, and one Python API across OpenAI, Anthropic, Google, Bedrock, Azure, Groq, Mistral, xAI and Ollama. The tradeoff: it is Python-only, with no equivalent multi-language support.
Where it improves on AutoGen
- +Agent permissions · YesTools can be marked as requiring human approval, and the run pauses with the pending calls so a person approves or denies each one before the tool body executes; the docs also warn approval is not an authorization boundary.Source ↗
- +Claude · YesAnthropic is a first-class built-in provider with its own model class and install extra, selectable by a provider-prefixed model string like anthropic:claude-sonnet-4-6.Source ↗
- +Open models · YesOpen-weight models are reachable through OpenAI-compatible providers the docs enumerate, including local runtimes Ollama and vLLM as well as Hugging Face and Groq, so weights you host yourself are supported.Source ↗
Trade-offs against AutoGen
- −Writes code · PartlyThe framework itself is a Python SDK, but its Harness ships a Coder capability whose file tools let an agent author and edit files in a workspace, so code writing comes from the bundled agent rather than a product you sign into.Source ↗
- −Getting out · PartlyPrepaid Gateway credits are non-refundable and expire after twelve months of account dormancy; Logfire data is exportable over its query API and Growth adds self-serve deletion.Source ↗
- 05
Letta
Stateful agent harness, cloud and SDK for agents with persistent, git-versioned memory.
From FreeWhy it's on this listDebugs and fixes · YesVendor states coding agents debug failures and run test suites.Source ↗
Where it improves on AutoGen
Trade-offs against AutoGen
- −MCP server · NoMCP runs inbound only: Letta sessions consume stdio, HTTP and SSE MCP servers; no Letta MCP server is published.Source ↗
- −Audit log · NoNo administrative audit log is published; the Enterprise list stops at RBAC, SSO, quotas and dedicated support.Source ↗
- −Getting out · PartlyMemory is git-backed files you can inspect and sync to your own GitHub repo; credit expiry is never stated.Source ↗
- 06
CrewAI
Open-source multi-agent framework with a managed platform for deploying and governing agent workflows.
From FreeWhy it's on this listFor the reader who wants a simpler role-based abstraction -- a "crew" of agents with defined roles -- plus a built-in governed platform, instead of assembling orchestration and governance themselves. CrewAI's own GitHub repo confirms MIT license and 57,400+ stars; its own pricing page confirms a free Basic tier (visual editor, AI copilot, GitHub integration, 50 workflow executions/month) and a custom-priced Enterprise tier with SSO, RBAC and PII redaction. The tradeoff: the free tier's execution cap pushes serious usage toward the custom-priced Enterprise plan.
Where it improves on AutoGen
- +Done-for-you service · PartlyYou run the software yourself, but the Enterprise plan sells forward-deployed engineers, onboarding and training separately, so people-delivered build help exists as a paid extra.Source ↗
- +Claude · YesAnthropic is one of the natively integrated providers, configured with your own key, and Claude models are also reachable through Bedrock and Snowflake Cortex.Source ↗
- +Open models · YesLocal and open-weight serving is documented end to end, with step-by-step Ollama setup plus Hugging Face, Together, Groq and local NVIDIA NIM examples via LiteLLM.Source ↗
Trade-offs against AutoGen
- −Writes code · PartlyAgents you build can author and run Python when code execution is switched on, but this is a capability of agents inside the framework rather than a product that ships code for you.Source ↗
- −Getting out · PartlyAutomation source can be pulled back as a ZIP over the API and traces can be shipped to your own OpenTelemetry collector; nothing published covers rollover of unused executions.Source ↗
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