AutoGen Studio is a low-code / no-code developer GUI from Microsoft Research for rapidly prototyping, composing, and debugging multi-agent AI workflows built on the AutoGen framework. Shipped as the `autogenstudio` Python package and launched with `autogenstudio ui`, it serves a FastAPI + React (Gatsby) web app on localhost that exposes four primary interfaces — Team Builder, Playground, Gallery, and Deployment — backed by a SQLModel persistence layer (SQLite by default; any SQLAlchemy-compatible backend such as PostgreSQL, MySQL, MSSQL via `--database-uri`). The Team Builder offers drag-and-drop and JSON authoring of teams, agents, models, tools, and termination conditions fully aligned with AutoGen AgentChat's declarative component spec; the Playground streams live inter-agent messages and renders the control transition graph; the Gallery imports community components; and the Deployment view exports a team to Python, exposes it as an endpoint, and packages it for Docker. AutoGen Studio is built on AutoGen AgentChat / Core / Extensions and supports any OpenAI-compatible model endpoint (OpenAI, Azure OpenAI, Anthropic, local vLLM/Ollama, etc.) via declarative `model_client` configuration, plus MCP tool integration. Authentication is experimental (GitHub OAuth + JWT only). Microsoft explicitly positions AutoGen Studio as a research prototype — not production-ready — and encourages teams that need authn/z, multi-tenancy, sandboxing rigor, or hardened deployment to build directly on the AutoGen framework instead. Companion to the broader AutoGen multi-agent framework, distributed under the Microsoft microsoft/autogen monorepo (CC-BY-4.0 docs, MIT code).
AutoGen Studio is profiled on the APIs.io network. Tagged areas include AutoGen, AutoGen Studio, Multi-Agent, Agent Framework, and AI Agents.
AutoGen Studio’s developer surface includes engineering blog, documentation, FAQ, and 19 more developer resources.
Regulatory Posture applies to this provider. Its tags matched the
Horizontal (data, software, accessibility, platform) regime, so
Regulatory Posture carries 15 points of the composite.
If this regime is wrong for your business, say so on your
provider repo — the
applicability map is public and we will correct it.
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for
this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero:
never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and
several others — scorable at all.
The six quality facets above are damped to 85 points between them,
because the conditional facet above carries the other
15. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 85% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
Installable via `pip install -U autogenstudio` (Python 3.10+); current PyPI release 0.4.2.2
Launched as a local web app with `autogenstudio ui --port 8081` (FastAPI backend + Gatsby/React frontend)
Configurable via `--host`, `--port`, `--appdir`, `--reload`, `--database-uri`, `--upgrade-database`, `--auth-config`
Team Builder visual canvas with drag-and-drop assembly of teams, agents, models, tools, and termination conditions, plus equivalent direct JSON editing
Playground with live inter-agent message streaming, control transition graph visualization, UserProxyAgent sessions, and pause/stop run control
Gallery for discovering and importing community-created components and third-party integrations
Deployment view that exports a team to Python code, exposes it as a runnable endpoint, and supports containerized execution via Docker
Bring-your-own model — any OpenAI-compatible endpoint (OpenAI, Azure OpenAI, Anthropic, vLLM, Ollama, local models) via declarative `model_client` config; AutoGen Extensions provides first-party clients
Define agents in Python with AutoGen AgentChat, dump to JSON via `dump_component().model_dump_json()`, and import into Studio's JSON editor
MCP (Model Context Protocol) tool integration via `autogenstudio/mcp` and `/api/mcp` routes
SQLModel-based persistence (Pydantic + SQLAlchemy) — defaults to SQLite, supports PostgreSQL, MySQL, MSSQL, Oracle, and other SQLAlchemy dialects
Internal FastAPI surface (not a public API) under `/api/` with routes for teams, sessions, runs, gallery, mcp, settings, validation, and a `/api/ws` WebSocket for streaming
Experimental GitHub OAuth authentication with JWT (`--auth-config auth.yaml`); disabled by default, WebSockets require `?token=` query param when enabled
Default app directory `~/.autogenstudio/` for database and generated user files
Dev container shipped under `python/packages/autogen-studio/.devcontainer/` for source builds
{"Frontend stack" => "React + Gatsby (built with `yarn build`); backend served by `autogenstudio.web.serve`"}
Explicitly positioned by Microsoft as a research prototype — not production-ready; lacks production-grade authn/z, multi-tenancy, jailbreak hardening, and least-privilege key scoping
Companion to the broader AutoGen framework (AgentChat, Core, Extensions, .NET) under the microsoft/autogen monorepo (~58k GitHub stars)
Original research prototype (Oct 2023) by Dibia, Bansal, Fourney, Choudhury, Amershi, Awadallah, Wang; EMNLP 2024 System Demonstrations paper
{"License" => "MIT for code, CC-BY-4.0 for documentation"}
aid: autogen-studio
name: AutoGen Studio
description: AutoGen Studio is a low-code / no-code developer GUI from Microsoft Research for rapidly prototyping, composing,
and debugging multi-agent AI workflows built on the AutoGen framework. Shipped as the `autogenstudio` Python package and
launched with `autogenstudio ui`, it serves a FastAPI + React (Gatsby) web app on localhost that exposes four primary interfaces
— Team Builder, Playground, Gallery, and Deployment — backed by a SQLModel persistence layer (SQLite by default; any SQLAlchemy-compatible
backend such as PostgreSQL, MySQL, MSSQL via `--database-uri`). The Team Builder offers drag-and-drop and JSON authoring
of teams, agents, models, tools, and termination conditions fully aligned with AutoGen AgentChat's declarative component
spec; the Playground streams live inter-agent messages and renders the control transition graph; the Gallery imports community
components; and the Deployment view exports a team to Python, exposes it as an endpoint, and packages it for Docker. AutoGen
Studio is built on AutoGen AgentChat / Core / Extensions and supports any OpenAI-compatible model endpoint (OpenAI, Azure
OpenAI, Anthropic, local vLLM/Ollama, etc.) via declarative `model_client` configuration, plus MCP tool integration. Authentication
is experimental (GitHub OAuth + JWT only). Microsoft explicitly positions AutoGen Studio as a research prototype — not production-ready
— and encourages teams that need authn/z, multi-tenancy, sandboxing rigor, or hardened deployment to build directly on the
AutoGen framework instead. Companion to the broader AutoGen multi-agent framework, distributed under the Microsoft microsoft/autogen
monorepo (CC-BY-4.0 docs, MIT code).
type: Index
deliveryModel:
model: unknown
license_evidence:
not_product:
- microsoft/autogen
open_source: unknown
commercial: false
callable_host: false
label: Delivery model not determined — needs a product licence on record
confidence: low
source:
- repository-not-product
generated: '2026-09-25'
method: derived
accessModel:
pricing: unknown
onboarding: unknown
trial: false
try_now: false
public: false
label: Unknown
confidence: low
source: []
generated: '2026-07-22'
method: derived
position: Producing
access: Open Source
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/autogen-studio.png
tags:
- AutoGen
- AutoGen Studio
- Multi-Agent
- Agent Framework
- AI Agents
- Low-Code
- No-Code
- GUI
- Visual Builder
- Drag And Drop
- Prototyping
- AgentChat
- Microsoft Research
- Python
- FastAPI
- React
- SQLModel
- MCP
- Open Source
tags_raw:
- AutoGen
- AutoGen Studio
- Multi-Agent
- Agent Framework
- Agentic AI
- Low-Code
- No-Code
- GUI
- Visual Builder
- Drag and Drop
- Prototyping
- AgentChat
- Microsoft Research
- Python
- FastAPI
- React
- SQLModel
- MCP
- Open Source
- Open-Source
url: https://raw.githubusercontent.com/api-evangelist/autogen-studio/refs/heads/main/apis.yml
created: '2026-05-24'
modified: '2026-05-24'
specificationVersion: '0.23'
apis: []
common:
- type: Releases
url: https://github.com/microsoft/autogen/releases
- type: SecurityPolicy
url: https://github.com/microsoft/autogen/blob/main/SECURITY.md
- type: CodeOfConduct
url: https://github.com/microsoft/autogen/blob/main/CODE_OF_CONDUCT.md
- type: ContributionGuide
url: https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md
- url: https://microsoft.github.io/autogen/0.2/blog/rss.xml
type: Blog
- type: Website
url: https://microsoft.github.io/autogen/
- type: Documentation
url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/index.html
- type: Installation
url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/installation.html
- type: Usage
url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/usage.html
- type: ExperimentalFeatures
url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/experimental.html
- type: FAQ
url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/faq.html
- type: GitHubRepository
url: https://github.com/microsoft/autogen
- type: SourceCode
url: https://github.com/microsoft/autogen/tree/main/python/packages/autogen-studio
- type: PackagePyPI
url: https://pypi.org/project/autogenstudio/
- type: GitHubOrganization
url: https://github.com/microsoft
- type: Discord
url: https://aka.ms/autogen-discord
- type: Twitter
url: https://twitter.com/pyautogen
- type: VideoTutorial
url: https://youtu.be/oum6EI7wohM
- type: ResearchPaper
url: https://aclanthology.org/2024.emnlp-demo.8/
- type: RoadMap
url: https://github.com/microsoft/autogen/issues
- type: License
url: https://github.com/microsoft/autogen/blob/main/LICENSE-CODE
- type: Companion
url: https://github.com/api-evangelist/microsoft-autogen
- type: Features
data:
- Installable via `pip install -U autogenstudio` (Python 3.10+); current PyPI release 0.4.2.2
- Launched as a local web app with `autogenstudio ui --port 8081` (FastAPI backend + Gatsby/React frontend)
- Configurable via `--host`, `--port`, `--appdir`, `--reload`, `--database-uri`, `--upgrade-database`, `--auth-config`
- Team Builder visual canvas with drag-and-drop assembly of teams, agents, models, tools, and termination conditions, plus
equivalent direct JSON editing
- Component Library backed by AutoGen AgentChat's declarative component spec (teams, agents, models, tools, termination
conditions)
- Playground with live inter-agent message streaming, control transition graph visualization, UserProxyAgent sessions, and
pause/stop run control
- Gallery for discovering and importing community-created components and third-party integrations
- Deployment view that exports a team to Python code, exposes it as a runnable endpoint, and supports containerized execution
via Docker
- Bring-your-own model — any OpenAI-compatible endpoint (OpenAI, Azure OpenAI, Anthropic, vLLM, Ollama, local models) via
declarative `model_client` config; AutoGen Extensions provides first-party clients
- Define agents in Python with AutoGen AgentChat, dump to JSON via `dump_component().model_dump_json()`, and import into
Studio's JSON editor
- MCP (Model Context Protocol) tool integration via `autogenstudio/mcp` and `/api/mcp` routes
- SQLModel-based persistence (Pydantic + SQLAlchemy) — defaults to SQLite, supports PostgreSQL, MySQL, MSSQL, Oracle, and
other SQLAlchemy dialects
- Internal FastAPI surface (not a public API) under `/api/` with routes for teams, sessions, runs, gallery, mcp, settings,
validation, and a `/api/ws` WebSocket for streaming
- Experimental GitHub OAuth authentication with JWT (`--auth-config auth.yaml`); disabled by default, WebSockets require
`?token=` query param when enabled
- Default app directory `~/.autogenstudio/` for database and generated user files
- Dev container shipped under `python/packages/autogen-studio/.devcontainer/` for source builds
- Frontend stack: React + Gatsby (built with `yarn build`); backend served by `autogenstudio.web.serve`
- Explicitly positioned by Microsoft as a research prototype — not production-ready; lacks production-grade authn/z, multi-tenancy,
jailbreak hardening, and least-privilege key scoping
- Companion to the broader AutoGen framework (AgentChat, Core, Extensions, .NET) under the microsoft/autogen monorepo (~58k
GitHub stars)
- Original research prototype (Oct 2023) by Dibia, Bansal, Fourney, Choudhury, Amershi, Awadallah, Wang; EMNLP 2024 System
Demonstrations paper
- License: MIT for code, CC-BY-4.0 for documentation
sources:
- https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/index.html
- https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/installation.html
- https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/usage.html
- https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/experimental.html
- https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/faq.html
- https://github.com/microsoft/autogen/tree/main/python/packages/autogen-studio
- https://pypi.org/project/autogenstudio/
maintainers:
- FN: Kin Lane
email: kin@apievangelist.com
x-parent: autogen
x-relationship: product
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