# AutoGen Studio

**Canonical:** https://apis.io/providers/autogen-studio/  
**Website:** https://microsoft.github.io/autogen/  
**APIs profiled:** 0

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).

## Kin Score — 12.8 / 100 (emerging)

Scored 2026-08-19 under rubric 0.12.0. Trend: flat (+0.0 from 12.8).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 34.2 |
| Developer Ergonomics | 16.7 |
| Commercial Clarity | 0.0 |
| Access Clarity | 0.0 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Tags

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

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/autogen-studio/). Scores are computed from the provider's own public artifacts under a published rubric.