Skip to main content
hc
Submit
toolsSource-backedReview first Safety ✓ Privacy ✓
Microsoft logo

Microsoft AutoGen

Open-source framework for building multi-agent AI applications, conversations, workflows, and autonomous systems.

by Microsoft·added 2026-04-27·
CLI
HarnessCLI
Review first — review before installing

Open the source and read safety notes before installing.

Citation facts

Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.

Canonical URL
https://heyclau.de/entry/tools/microsoft-autogen
Source URLs
https://microsoft.github.io/autogen/stable/, https://github.com/microsoft/autogen, https://microsoft.github.io/autogen/
Brand
Microsoft
Brand domain
microsoft.github.io
Brand asset source
brandfetch
Safety notes
AutoGen runs multi-agent workflows that can execute code and call external tools autonomously; sandbox execution and review agent actions before granting tool or system access.
Privacy notes
AutoGen agents send prompts, code, and tool outputs to the configured LLM provider(s); review what data your agents transmit and each provider's data-handling and retention terms.
Author
Microsoft
Claim status
unclaimed
Last verified
2026-04-27

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Compare context
Selected

0

Current score

78

Baseline

—

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Complete

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    Done

  • Source provenance statusRequired

    Marked as source-backed.

    Done

  • Metadata reviewed

    Registry metadata indicates a reviewed listing.

    Done

Safety and privacy checks

Complete

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    Review the listed safety guidance before running commands.

    Done

  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done

  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done

  • Package verification flag

    No package verification flag provided.

    Pending

  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending

  • Baseline comparison available

    No baseline peer selected yet.

    Pending

  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

Copy & paste

Copy-ready — paste the snippet to get started.

Install command

Not provided

Config snippet

Not provided

Copy snippet

Provided

Prerequisites

None

Platforms

1 listed

Install type

Copy & paste

Adoption plan

Balanced adoption plan

Current risk score 16/100. Use staged verification before broader rollout.

Risk 16

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done

  • Confirm metadata review state

    Listing has review metadata.

    Done

  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes are present.

    Done

  • Review privacy notesRequired

    Privacy notes are present.

    Done

  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending

  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending

  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Required evidence gates are covered (5/6 signals complete).

Risk 15

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Present

Review metadata is present.

Required in this preset

Safety notes

Present

Safety notes are present.

Required in this preset

Privacy notes

Present

Privacy notes are present.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required evidence gates are covered for this preset.

Decision timeline

Decision timeline · balanced

5/6 steps complete with no blocking gaps for this preset.

Risk 14

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is available.

Done

verify

Review safety notesRequired

Safety notes are available.

Done

verify

Review privacy notes

Privacy notes are available.

Done

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

No required blockers for this timeline preset.

Safety & privacy surface

Safety & privacy surface

1 safety and 1 privacy notes across 2 risk areas. Review closely: permissions & scopes, third-party handling.

2 areas
  • SafetyPermissions & scopesAutoGen runs multi-agent workflows that can execute code and call external tools autonomously; sandbox execution and review agent actions before granting tool or system access.
  • PrivacyThird-party handlingAutoGen agents send prompts, code, and tool outputs to the configured LLM provider(s); review what data your agents transmit and each provider's data-handling and retention terms.

Disclosure: editorial

Safety notes

  • AutoGen runs multi-agent workflows that can execute code and call external tools autonomously; sandbox execution and review agent actions before granting tool or system access.

Privacy notes

  • AutoGen agents send prompts, code, and tool outputs to the configured LLM provider(s); review what data your agents transmit and each provider's data-handling and retention terms.

Schema details

Install type
copy
Troubleshooting
No
Source repository stats
Scope
Source repo
Tool listing metadata
Pricing
open-source
Disclosure
editorial
Application category
DeveloperApplication
Operating system
macOS, Windows, Linux
Full copyable content
## Editorial notes

AutoGen is a useful reference for multi-agent application patterns, especially where conversation loops and coordination matter.

## Disclosure

Editorial listing. No paid placement or affiliate link is used.

About this resource

Editorial notes

AutoGen is a useful reference for multi-agent application patterns, especially where conversation loops and coordination matter.

Disclosure

Editorial listing. No paid placement or affiliate link is used.

#agent-framework#multi-agent

Source citations

Add this badge to your README

Show that Microsoft AutoGen is listed on HeyClaude. Paste this Markdown into your README — it renders the badge and links back to this page.

Listed on HeyClaude
[![Listed on HeyClaude](https://heyclau.de/badge/tools/microsoft-autogen.svg)](https://heyclau.de/entry/tools/microsoft-autogen)

How it compares

Microsoft AutoGen side by side with 2 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

1 trust signal differ across this comparison (Submitter).

Field
Microsoft logoMicrosoft AutoGen

Open-source framework for building multi-agent AI applications, conversations, workflows, and autonomous systems.

Open dossier
LangGraph logoLangGraph

Agent orchestration framework for building stateful, controllable, multi-step LLM and agent workflows.

Open dossier
Prompt flow logoPrompt flow

Open-source suite of development tools from Microsoft for building LLM applications end to end — create executable flows that link LLMs, prompts, Python, and tools, trace and debug them, evaluate quality against datasets in CI/CD, and deploy to a serving platform.

Open dossier
Next steps
Open dossierAPI JSONOpen LLMOpen sourceNewsletterClaim listing
Open dossierAPI JSONOpen LLMOpen sourceNewsletterClaim listing
Open dossierAPI JSONOpen LLMOpen sourceNewsletterClaim listing
Trust
Review statusReviewedMaintainer reviewedReviewedMaintainer reviewedReviewedMaintainer reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backed
SubmitterDiffers——davion-knight
Install riskReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety · Privacy ✓ Safety ✓ Privacy ✓
BrandMicrosoft logoMicrosoftLangGraph logoLangGraphPrompt flow logoPrompt flow
Categorytoolstoolstools
Sourcesource-backedsource-backedsource-backed
AuthorMicrosoftLangChainmicrosoft
Added2026-04-272026-04-272026-07-10
Platforms
CLI
CLI
CLI
Source repo———
Safety notes✓AutoGen runs multi-agent workflows that can execute code and call external tools autonomously; sandbox execution and review agent actions before granting tool or system access.— missing✓Flows execute nodes that run LLM prompts, Python code, and tools, so review what a flow does before running it, especially flows from untrusted sources or over untrusted input. Connections store model-provider credentials; scope them to the minimum needed and keep connection configuration out of source control. Treat flow inputs and LLM outputs as untrusted for downstream actions, and gate any node that writes data or calls external services. Evaluation and tracing capture prompts, inputs, and outputs; confirm what is recorded and where before running on sensitive data. Keep production flows, connections, and permissions narrower than sample flows and notebooks.
Privacy notes✓AutoGen agents send prompts, code, and tool outputs to the configured LLM provider(s); review what data your agents transmit and each provider's data-handling and retention terms.✓LangGraph sends prompts and graph state to your configured model provider (including Claude); persisted state and checkpoints can contain message and tool-call data.✓Running a flow sends prompts and inputs to the configured model providers, which process that data under their own terms. Traces, batch runs, and evaluation results can record prompts, inputs, outputs, and metadata, so choose retention and access controls for where those are stored. Connection secrets, evaluation datasets, and exported run data should be treated as sensitive and kept out of version control. The optional Azure AI cloud version processes flow and run data under its terms; running locally keeps that data in your environment.
Prerequisites— none listed— none listed
  • Python project and a package manager to install the `promptflow` SDK and CLI from PyPI (a VS Code extension is also available).
  • Model-provider credentials configured as connections for the LLMs your flows call.
  • Test and evaluation datasets with expected outputs if you want to measure flow quality.
  • A serving target or application codebase for deployment, and optionally an Azure AI workspace for the cloud version.
Install———
Config———
Citations
ClaimUnclaimedUnclaimedUnclaimed
Open 3 picks in the interactive comparison tool

Related guides

Source-backed guides for putting this to work.

Microsoft logoguides

Microsoft AI Agents for Beginners

Learn AI agents through Microsoft's course covering frameworks, design patterns, tool use, agentic RAG, production, protocols, memory, and security.

Review firstSource-backedReview firstAdded 26d ago
Safety ✓ Privacy ✓by Microsoft

Signals

Loading live community signals…

More like this, weekly

A short, calm digest of reviewed Claude resources. Unsubscribe any time.