Portfolio concentration
77%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
30 repos
Visible snapshot
3 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (13), Unknown (7), Jupyter Notebook (4)
Average size
27
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
77%
of the visible star count comes from this organization's top three repositories.
27
stars per repository in this same snapshot.
Python
is the most common language here, with 3 repositories updated in the last 90 days.
Why this rank
This organization stands out because one flagship repo drives 62% of its visible star count.
Organization pages work best when you separate portfolio breadth from flagship concentration. In crewAI's case, the visible top three repositories account for about 77% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Python (13), Unknown (7), Jupyter Notebook (4). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
| # | Repository | Language | Stars |
|---|---|---|---|
| 1 | crewaiinc/awesome-crewai A curated list of open-source projects built by the CrewAI community. Discover, contribute, and extend the possibilities of AI agents with CrewAI. | 511 | |
| 2 | crewaiinc/crewAI-quickstarts A comprehensive collection of CrewAI quickstarts and feature demos designed to help developers learn and master the CrewAI framework through hands-on examples. | Jupyter Notebook | 66 |
| 3 | crewaiinc/enterprise-mcp-server MCP Server for kicking off and getting status of your crew deployments | Python | 58 |
| 4 | crewaiinc/skills | 37 | |
| 5 | crewaiinc/companies-powered-by-crewai A showcase of companies and platforms leveraging CrewAI to power their AI solutions and workflows. | 27 | |
| 6 | crewaiinc/marketplace-crew-template | Python | 23 |
| 7 | crewaiinc/template_deep_research | Python | 20 |
| 8 | crewaiinc/marketplace-flow-template | Python | 10 |
| 9 | crewaiinc/crewai-enterprise-trigger-examples | Python | 7 |
| 10 | crewaiinc/template_conversational_example Demo example of a crew with a conversational interface | HTML | 7 |
| 11 | crewaiinc/template_pull_request_review | Python | 7 |
| 12 | crewaiinc/hackaton-demos | Jupyter Notebook | 6 |
| 13 | crewaiinc/nvidia-nemotron-demo | Jupyter Notebook | 5 |
| 14 | crewaiinc/agent-control | 5 | |
| 15 | crewaiinc/nvidia-demo | Jupyter Notebook | 5 |
| 16 | crewaiinc/course-generator A production-ready example of CrewAI's Flow + Crew hybrid pattern for educational content | Python | 4 |
| 17 | crewaiinc/qdrant_rag_chat_app Frontend for CrewAI Rag Application | Python | 4 |
| 18 | crewaiinc/llamacon-hackthon | HTML | 4 |
| 19 | crewaiinc/crewai_training_step_by_step | Python | 3 |
| 20 | crewaiinc/crewai-omniauth-okta OAuth2 strategy for Okta with updated code that allows using the default "Org Authorization Server" for accounts that do not have the "API Access Management" paid feature enabled. Source: https://github.com/omniauth/omniauth-okta/pull/31/files | Ruby | 3 |
| 21 | crewaiinc/crew-action-2026-03 | TypeScript | 2 |
| 22 | crewaiinc/template_frontend_crewai_flows_streamlit_ui | Python | 2 |
| 23 | crewaiinc/crewai-community-tools | 2 | |
| 24 | crewaiinc/template_research_agent | 1 | |
| 25 | crewaiinc/template_job_fit_assessment Job Fit Assessment demo app | Python | 1 |
| 26 | crewaiinc/template_support_ticket_front | CSS | 1 |
| 27 | crewaiinc/Corsair_SnowflakeProject | Python | 1 |
| 28 | crewaiinc/Madison-Reed-MVP | Python | 1 |
| 29 | crewaiinc/sqlite Read-only mirror of https://gitlab.com/cznic/sqlite | 0 | |
| 30 | crewaiinc/crewai-lab | HTML | 0 |
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.