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 CLI, engineering blog, documentation, getting-started guide, FAQ, and 25 more developer resources.
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Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for
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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
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Agent readiness — checks not met, largest first (exact, from this profile):
Machine-Readable Auth+10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
Idempotency+9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics+8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
13 more unmet checks in the Agent Readiness table above.
Kin Score — facets with the most composite points still available (weight × headroom):
Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.
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
probe_state: covered
source: []
generated: '2026-11-06'
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
- Agent Chat
- 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: '2026-11-05'
specificationVersion: '0.23'
maintainers:
- FN: Kin Lane
email: kin@apievangelist.com
common:
- type: CLI
url: cli/autogen-studio-cli.yml
- type: Hosts
url: hosts/autogen-studio-hosts.yml
- type: Vendors
url: vendors/autogen-studio-vendors.yml
- type: SDKs
url: packages/autogen-studio-packages.yml
- type: Packages
url: packages/autogen-studio-packages.yml
- 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: SourceCode
url: https://github.com/microsoft/autogen/tree/main/python/packages/autogen-studio
- type: GitHubOrganization
url: https://github.com/microsoft
- type: GettingStarted
url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/installation.html
- type: FAQ
url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/faq.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: 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/
apis: []
x-parent: autogen
x-relationship: product
x-enrichment:
date: '2026-11-05'
status: enriched
artifacts_added: 2
pass: local-v6
x-coverage:
state: covered
reason: covered
detail: AutoGen Studio is a locally run open-source GUI (pip package + CLI) with no hosted or published API contract; packages
and CLI were recorded from PyPI and the Studio docs.
evidence:
- url: https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/installation.html
status: 200
checked: '2026-11-05'
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