- Builders evaluating this category
Agents
MetaGPT
Multi-agent framework that simulates a software company with PM, architect, engineer, and QA roles.
50K Stars
MIT License
geekan Maintainer
2026-06-16 Verified
Overview
What is MetaGPT?
Multi-agent framework that simulates a software company with PM, architect, engineer, and QA roles.
FAQ
Frequently asked questions
What should I check before using MetaGPT?
Build one two-step agent flow with a tool call, a state transition, and an observable failure path.
Is MetaGPT open source?
MetaGPT is listed on OpenAgent.bot with MIT based on the current resource metadata. Re-check the official repository, docs, and license before production use.
Decision brief
JSON
Should you use MetaGPT?
- Production adoption without checking source links, permissions, and maintenance.
- Verified 2026-06-16
- License: MIT
- Repo: geekan/MetaGPT
- Open-source signal
Deployment
Check source
Permission surface
Low explicit permission surface in metadata
Decision signals
Local first, CLI
Agent packet
Structured decision data for MetaGPT
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
workflow orchestration, automation
Constraints
open source
Deployment
Check source
Permission surface
Low explicit permission surface in metadata
Recommended workflows
developer workflow, production agent
Overview
What MetaGPT does
What it is
MetaGPT is a agent in the agents category. Multi-agent framework that simulates a software company with PM, architect, engineer, and QA roles.
Why it matters
MetaGPT matters when builders need a clearer way to choose tools by workflow fit, constraints, source quality, and operational risk rather than by category labels alone.
How to evaluate it
Evaluate MetaGPT by starting from the official sources, checking its interface surface, and running one narrow workflow before expanding scope.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type agent
Category Agents
Maturity active
Difficulty Unknown
License MIT
Pricing open source
Verified 2026-06-16
Source confidence medium
Risk level moderate
Fit matrix
Where MetaGPT fits in an agent stack
partial
Browser automation
MetaGPT has at least one signal for browser automation, but should be checked against a real task before adoption.
- Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Coding agent workflow
MetaGPT has at least one signal for coding agent workflow, but should be checked against a real task before adoption.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Reusable skill workflow
MetaGPT has at least one signal for reusable skill workflow, but should be checked against a real task before adoption.
- Run one skill end to end and check whether it produces evidence or structured output.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Connector or protocol layer
MetaGPT is not primarily positioned for connector or protocol layer in the current metadata.
- Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Evaluation and observability
MetaGPT is not primarily positioned for evaluation and observability in the current metadata.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Local or private AI stack
MetaGPT is not primarily positioned for local or private ai stack in the current metadata.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Official setup instructions and a small real workflow
Likely outputs
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
MetaGPT is listed as open source.
License metadata: MITMetaGPT has a recorded GitHub repository: geekan/MetaGPT.
Resource facts and GitHub source link.- Dedicated docs link is missing.
- Repository freshness has not been recorded.
Next action
How to start evaluating MetaGPT
Inspect repository
Check license, recent activity, issues, examples, and security-sensitive code paths.
Open source Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about MetaGPT
What is MetaGPT used for?
MetaGPT is used as a agent for agents workflows. The most relevant recorded capabilities are workflow orchestration, automation.
Is MetaGPT open source?
MetaGPT is listed as open source with MIT license metadata. Re-check the official repository or source link before production use.
Can agents use MetaGPT directly?
MetaGPT has recorded interfaces such as official source links. Agents should prefer the JSON or Markdown profile first, then follow official docs for real execution.
What should I check before production use?
Check source confidence (medium), risk level (moderate), license, maintenance freshness, permission surface, required credentials, and whether the first workflow succeeds in a sandbox.