--- title: "camel vs agency" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/camel-ai-camel-vs-operand-agency" tools: ["camel-ai-camel", "operand-agency"] --- # camel vs agency *GraphCanon updated Aug 21, 2026* ## Verdict Pick camel if cAMEL exemplifies a pioneering multi-agent framework designed to foster advanced interaction among AI agents through collaboration, communication, and learning; pick agency if agency is a fast and minimal Python-based framework for developing agentic systems that excels in its streamlined approach to creating autonomous agents. [camel](https://docs.camel-ai.org/) reports 18k GitHub stars, 2.0k forks, and 471 open issues, last pushed Aug 14, 2026. [agency](https://createwith.agency) has 489 stars, 28 forks, and 19 open issues, last pushed Jun 10, 2026. Figures are from public GitHub metadata via [camel's repository](https://github.com/camel-ai/camel) and [agency's repository](https://github.com/operand/agency). | | [camel](/tools/camel-ai-camel.md) | [agency](/tools/operand-agency.md) | | --- | --- | --- | | Tagline | CAMEL: The first and the best multi-agent framework | A fast and minimal framework for building agentic systems | | Stars | 17,592 | 489 | | Forks | 2,042 | 28 | | Open issues | 471 | 19 | | Language | Python | Python | | Adopt for | CAMEL exemplifies a pioneering multi-agent framework designed to foster advanced interaction among AI agents through collaboration, communication, and learning. | Agency is a fast and minimal Python-based framework for developing agentic systems that excels in its streamlined approach to creating autonomous agents. | | Persona | - | - | | Runtime | - | - | | License | The project uses the Apache 2.0 license, allowing free use, modification, and distribution. It comes with no warranty. | MIT | | Categories | AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [camel](/tools/camel-ai-camel.md) | [agency](/tools/operand-agency.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 2d | 71d | | Open issues (now) | 471 | 19 | | Stars delta | +178 (30d) | +2 (30d) | | Open issues delta | +4 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/camel-ai-camel/trust.md) | [trust report](/tools/operand-agency/trust.md) | ## Shared compatibility - **Python**: [camel](/tools/camel-ai-camel.md) - Python runtime; [agency](/tools/operand-agency.md) - Python runtime ## Decision facts: camel - **Requirements:** Installation is straightforward through PyPI. Ensure Python and pip are installed before running 'pip install camel-ai'. - **Adopt for:** CAMEL exemplifies a pioneering multi-agent framework designed to foster advanced interaction among AI agents through collaboration, communication, and learning. - **License detail:** The project uses the Apache 2.0 license, allowing free use, modification, and distribution. It comes with no warranty. ## Decision facts: agency - **Adopt for:** Agency is a fast and minimal Python-based framework for developing agentic systems that excels in its streamlined approach to creating autonomous agents. ## Choose when ### Choose camel if… - License: camel is Apache-2.0, agency is MIT. - Requirements: Installation is straightforward through PyPI. Ensure Python and pip are installed before running 'pip install camel-ai'.. - Tags unique to camel: agent, communicative-ai, cooperative-ai, deep-learning. - You should consider using CAMEL if you are involved in developing scenarios where multiple AI agents need to collaborate effectively. It is well-suited for real-world applications such as managing IT/ ### Choose agency if… - License: agency is MIT, camel is Apache-2.0. - Tags unique to agency: actor-model, agent-framework, autonomous-agents. - When you prefer a lightweight solution for building autonomous agent systems without the need for extensive configuration or complex dependencies. ## When NOT to use camel - Avoid using CAMEL if your project does not require interactions among multiple agents or if scalability of the multi-agent system is not a priority. - Do not opt for CAMEL when you need focused single-agent AI capabilities, as its design centers on multi-agent environments and may impose unnecessary complexity. ## When NOT to use agency - If your development requires deeply integrated functionalities that would necessitate a heavier, more feature-rich framework. - In scenarios where you need robust tooling for large-scale deployment and management as Agency does not offer extensive LLMOps (LLM Operations) capabilities beyond its minimalistic design. ## Common questions ### What is the difference between camel and agency? camel: CAMEL: The first and the best multi-agent framework. agency: A fast and minimal framework for building agentic systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose camel over agency? Choose camel over agency when License: camel is Apache-2.0, agency is MIT; Requirements: Installation is straightforward through PyPI. Ensure Python and pip are installed before running 'pip install camel-ai'.; Tags unique to camel: agent, communicative-ai, cooperative-ai, deep-learning; You should consider using CAMEL if you are involved in developing scenarios where multiple AI agents need to collaborate effectively. It is well-suited for real-world applications such as managing IT/. ### When should I choose agency over camel? Choose agency over camel when License: agency is MIT, camel is Apache-2.0; Tags unique to agency: actor-model, agent-framework, autonomous-agents; When you prefer a lightweight solution for building autonomous agent systems without the need for extensive configuration or complex dependencies. ### When should I avoid camel? Avoid using CAMEL if your project does not require interactions among multiple agents or if scalability of the multi-agent system is not a priority. Do not opt for CAMEL when you need focused single-agent AI capabilities, as its design centers on multi-agent environments and may impose unnecessary complexity. ### When should I avoid agency? If your development requires deeply integrated functionalities that would necessitate a heavier, more feature-rich framework. In scenarios where you need robust tooling for large-scale deployment and management as Agency does not offer extensive LLMOps (LLM Operations) capabilities beyond its minimalistic design. ### Is camel or agency more popular on GitHub? camel has more GitHub stars (17,592 vs 489). Stars measure visibility, not whether either tool fits your constraints. ### Are camel and agency open source? Yes - both are open-source projects on GitHub (camel: Apache-2.0, agency: MIT). ### Where can I find alternatives to camel or agency? GraphCanon lists graph-backed alternatives at [camel alternatives](/tools/camel-ai-camel/alternatives) and [agency alternatives](/tools/operand-agency/alternatives) ([camel markdown twin](/tools/camel-ai-camel/alternatives.md), [agency markdown twin](/tools/operand-agency/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/camel-ai-camel-vs-operand-agency.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, camel or agency? camel: Very active. agency: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for camel and agency? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [camel trust report](/tools/camel-ai-camel/trust); [agency trust report](/tools/operand-agency/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=camel-ai-camel`](/api/graphcanon/graph?tool=camel-ai-camel) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_