--- title: "agent-protocol vs agency-orchestrator" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agi-inc-agent-protocol-vs-jnmetacode-agency-orchestrator" tools: ["agi-inc-agent-protocol", "jnmetacode-agency-orchestrator"] --- # agent-protocol vs agency-orchestrator *GraphCanon updated Sep 20, 2026* ## Verdict Pick agent-protocol if agent-protocol provides a standardized interface for interacting with various AI agents regardless of their underlying tech stack, aiming to ease development, deployment, and benchmarking; pick agency-orchestrator if agency Orchestrator is an AI workflow orchestrator that automatically collaborates among multiple AI agents based on user inputs, supports various large language models, and allows for zero-code YAML configuration. [agent-protocol](https://agentprotocol.ai) reports 1.5k GitHub stars, 186 forks, and 49 open issues, last pushed Apr 8, 2025. [agency-orchestrator](https://ao.aiolaola.com) has 2.3k stars, 303 forks, and 7 open issues, last pushed Sep 16, 2026. Figures are from public GitHub metadata via [agent-protocol's repository](https://github.com/agi-inc/agent-protocol) and [agency-orchestrator's repository](https://github.com/jnMetaCode/agency-orchestrator). | | [agent-protocol](/tools/agi-inc-agent-protocol.md) | [agency-orchestrator](/tools/jnmetacode-agency-orchestrator.md) | | --- | --- | --- | | Tagline | Common interface for AI agents | 🚀 One sentence → multi-AI-role collaboration → complete plan in minutes | | Stars | 1,454 | 2,274 | | Forks | 186 | 303 | | Open issues | 49 | 7 | | Language | Python | TypeScript | | Adopt for | agent-protocol provides a standardized interface for interacting with various AI agents regardless of their underlying tech stack, aiming to ease development, deployment, and benchmarking. | Agency Orchestrator is an AI workflow orchestrator that automatically collaborates among multiple AI agents based on user inputs, supports various large language models, and allows for zero-code YAML configuration. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents | AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-protocol](/tools/agi-inc-agent-protocol.md) | [agency-orchestrator](/tools/jnmetacode-agency-orchestrator.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 515d | 3d | | Open issues (now) | 49 | 7 | | Stars delta | -4 (30d) | +202 (30d) | | Open issues delta | -1 (30d) | -3 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/agi-inc-agent-protocol/trust.md) | [trust report](/tools/jnmetacode-agency-orchestrator/trust.md) | ## Decision facts: agent-protocol - **Adopt for:** agent-protocol provides a standardized interface for interacting with various AI agents regardless of their underlying tech stack, aiming to ease development, deployment, and benchmarking. ## Decision facts: agency-orchestrator - **Adopt for:** Agency Orchestrator is an AI workflow orchestrator that automatically collaborates among multiple AI agents based on user inputs, supports various large language models, and allows for zero-code YAML configuration. ## Choose when ### Choose agent-protocol if… - agent-protocol is primarily Python; agency-orchestrator is TypeScript. - License: agent-protocol is MIT, agency-orchestrator is Apache-2.0. - Tags unique to agent-protocol: agents, ai-agent, api, auto-gpt. - When you want to ensure interoperability between different AI agents irrespective of the frameworks used by them. ### Choose agency-orchestrator if… - agency-orchestrator is primarily TypeScript; agent-protocol is Python. - License: agency-orchestrator is Apache-2.0, agent-protocol is MIT. - Tags unique to agency-orchestrator: agency-agents, agent-orchestration, ai-agents, yaml-workflow. - Also covers Inference & Serving. - agency-orchestrator ships Docker support for self-hosted deployment. - agency-orchestrator ships an MCP server manifest. - You require automatic collaboration across a wide range of pre-defined expert roles (216+) to execute specific tasks efficiently. ## When NOT to use agent-protocol - If you are developing an isolated system with no intention to communicate or integrate with other AI agents outside this scope. - When working in environments where specific, proprietary interfaces provide significantly better performance or features than adhering to a generic protocol could offer. ## When NOT to use agency-orchestrator - If your workflow is simple or requires minimal collaboration; a single AI agent might suffice. - When you are working in an environment where there's high sensitivity around software licensing and the Apache-2.0 license poses compliance concerns. ## Common questions ### What is the difference between agent-protocol and agency-orchestrator? agent-protocol: Common interface for AI agents. agency-orchestrator: 🚀 One sentence → multi-AI-role collaboration → complete plan in minutes. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-protocol over agency-orchestrator? Choose agent-protocol over agency-orchestrator when agent-protocol is primarily Python; agency-orchestrator is TypeScript; License: agent-protocol is MIT, agency-orchestrator is Apache-2.0; Tags unique to agent-protocol: agents, ai-agent, api, auto-gpt; When you want to ensure interoperability between different AI agents irrespective of the frameworks used by them. ### When should I choose agency-orchestrator over agent-protocol? Choose agency-orchestrator over agent-protocol when agency-orchestrator is primarily TypeScript; agent-protocol is Python; License: agency-orchestrator is Apache-2.0, agent-protocol is MIT; Tags unique to agency-orchestrator: agency-agents, agent-orchestration, ai-agents, yaml-workflow; Also covers Inference & Serving; agency-orchestrator ships Docker support for self-hosted deployment; agency-orchestrator ships an MCP server manifest; You require automatic collaboration across a wide range of pre-defined expert roles (216+) to execute specific tasks efficiently. ### When should I avoid agent-protocol? If you are developing an isolated system with no intention to communicate or integrate with other AI agents outside this scope. When working in environments where specific, proprietary interfaces provide significantly better performance or features than adhering to a generic protocol could offer. ### When should I avoid agency-orchestrator? If your workflow is simple or requires minimal collaboration; a single AI agent might suffice. When you are working in an environment where there's high sensitivity around software licensing and the Apache-2.0 license poses compliance concerns. ### Is agent-protocol or agency-orchestrator more popular on GitHub? agency-orchestrator has more GitHub stars (2,274 vs 1,454). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-protocol and agency-orchestrator open source? Yes - both are open-source projects on GitHub (agent-protocol: MIT, agency-orchestrator: Apache-2.0). ### Where can I find alternatives to agent-protocol or agency-orchestrator? GraphCanon lists graph-backed alternatives at [agent-protocol alternatives](/tools/agi-inc-agent-protocol/alternatives) and [agency-orchestrator alternatives](/tools/jnmetacode-agency-orchestrator/alternatives) ([agent-protocol markdown twin](/tools/agi-inc-agent-protocol/alternatives.md), [agency-orchestrator markdown twin](/tools/jnmetacode-agency-orchestrator/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/agi-inc-agent-protocol-vs-jnmetacode-agency-orchestrator.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-protocol or agency-orchestrator? agent-protocol: Dormant. agency-orchestrator: Very active. 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 agent-protocol and agency-orchestrator? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-protocol trust report](/tools/agi-inc-agent-protocol/trust); [agency-orchestrator trust report](/tools/jnmetacode-agency-orchestrator/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agi-inc-agent-protocol`](/api/graphcanon/graph?tool=agi-inc-agent-protocol) - 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/_