CrewAIvsKoog
Generated from the two spec rows. Green marks the better value where a spec has a clear direction. Everything else is just different.
CrewAI
CrewAI · Agent framework
OSSMCP
Panel
6.64 spec wins
- Reliability
- 6.0
- Usefulness
- 6.5
- Cost
- 7.0
- Longevity
- 6.8
“The scaffold command is crewai create crew my_crew, the only place the word appears three times without a boat.”
Koog
JetBrains · Agent framework
OSSMCP
Panel
6.70 spec wins
- Reliability
- 6.3
- Usefulness
- 6.7
- Cost
- 7.7
- Longevity
- 6.0
“JetBrains runs a separate continuous integration job just for Ollama, which is more commitment to local models than most vendors manage.”
Spec by spec
| Spec | CrewAI | Koog |
|---|---|---|
| Architecture | ||
| Category | Agent framework | Agent framework |
| Runs | local, cloud | local |
| Platforms | macos, linux, windows | macos, linux, windows |
| Context window | not documented | not documented |
| Protocols | ||
| MCP client | Yes | Yes |
| MCP server | No | No |
| Capabilities | ||
| Runs terminal commands | No | No |
| Multi-file edits | No | No |
| Git operations | No | No |
| Browser control | YesMost crewai-tools web tools only scrape HTML, but StagehandTool drives a real browser with act, extract and observe primitives that click, type and fill forms. | No |
| Sandboxed execution | YesCodeInterpreterTool runs generated code in an isolated Docker container by default, and crewai-tools also ships E2B and Daytona sandbox tools; unsafe_mode=True opts out. | No |
| Multi-agent orchestration | Yes | Yes |
| Headless / CI mode | Yes | No |
| Models | ||
| Backbone | OpenAI, Anthropic, Ollama, any LiteLLM provider | any |
| Bring your own model | Yes | Yes |
| Local models | YesAn Agent's LLM takes a base_url, so Ollama at http://localhost:11434 or any OpenAI-compatible endpoint set through OPENAI_API_BASE works. | Yes |
| Cost | ||
| Pricing model | byok | byok |
| Starts at | $0/mo | n/a |
| Free tier | Yes | Yes |
| Bring your own key | Yes | Yes |
| Openness | ||
| Open source | Yes | Yes |
| License | MIT | Apache-2.0 |
| GitHub stars | 59,277 | 4,598 |
Which one would each critic pick
| Critic | CrewAI | Koog | Pick |
|---|---|---|---|
| El Juez | — | — | not enough reviews |
| El Amigo | 7.0 | 6.8 | CrewAI — Pick CrewAI if you think in roles and want a working multi-agent crew before dinner; pick LangGraph when you need to control every step and resume after a crash. |
| El Crítico | 6.3 | 6.0 | CrewAI — Agent behavior is defined in natural language fields, so a crew is a set of prompts wearing a class hierarchy, and a prompt-shaped system is tested by running it. |
| El Profesor | 6.3 | 6.8 | Koog — State can be restored at specific execution points rather than only at the start, and long conversations are shortened by explicit history compression instead of a truncation window. |
| La Inversora | 6.5 | 6.3 | CrewAI — Used by 65% of the Fortune 500 is the claim, a 45-day onboarding is the offer, and forward-deployed engineers a la carte is the business: a services company with a popular library on top. |
| La Jefa | 6.0 | 6.5 | Koog — It integrates with Spring Boot and Ktor, so it deploys into services we already run, and support goes through the vendor's existing issue tracker rather than a stranger's inbox. |
| El Hacker | 7.5 | 7.8 | Koog — Apache-2.0, one Maven coordinate, Ollama is in the provider list with its own continuous integration workflow, and agents can be exposed over ACP as well as consuming MCP tools. |
Picks are derived from each critic's own scores. Humans vote on matchups on the duels page.