--- title: "agentfield vs agent-starter-pack" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agent-field-agentfield-vs-googlecloudplatform-agent-starter-pack" tools: ["agent-field-agentfield", "googlecloudplatform-agent-starter-pack"] --- # agentfield vs agent-starter-pack *GraphCanon updated Jul 12, 2026* ## Verdict Pick agentfield if agent-Field/agentfield is a comprehensive toolset built in Go under the Apache-2.0 license, aiming to streamline the development lifecycle of scalable AI agents that are observably secure; pick agent-starter-pack if agent-starter-pack is a specialized toolset for deploying AI agents on the Google Cloud Platform with built-in CI/CD, evaluation tools, and observability features. [agentfield](http://www.agentfield.ai) reports 2.3k GitHub stars, 371 forks, and 91 open issues, last pushed Jul 10, 2026. [agent-starter-pack](http://goo.gle/agents-cli) has 6.5k stars, 1.5k forks, and 48 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [agentfield's repository](https://github.com/Agent-Field/agentfield) and [agent-starter-pack's repository](https://github.com/GoogleCloudPlatform/agent-starter-pack). | | [agentfield](/tools/agent-field-agentfield.md) | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | | --- | --- | --- | | Tagline | Build, run and scale AI agents like API and microservices | Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability. | | Stars | 2,339 | 6,514 | | Forks | 371 | 1,496 | | Open issues | 91 | 48 | | Language | Go | Python | | Adopt for | Agent-Field/agentfield is a comprehensive toolset built in Go under the Apache-2.0 license, aiming to streamline the development lifecycle of scalable AI agents that are observably secure. | agent-starter-pack is a specialized toolset for deploying AI agents on the Google Cloud Platform with built-in CI/CD, evaluation tools, and observability features. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents | AI Agents, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentfield](/tools/agent-field-agentfield.md) | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 91 | 48 | | Full report | [trust report](/tools/agent-field-agentfield/trust.md) | [trust report](/tools/googlecloudplatform-agent-starter-pack/trust.md) | ## Decision facts: agentfield - **Adopt for:** Agent-Field/agentfield is a comprehensive toolset built in Go under the Apache-2.0 license, aiming to streamline the development lifecycle of scalable AI agents that are observably secure. ## Decision facts: agent-starter-pack - **Requirements:** Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks. - **Adopt for:** agent-starter-pack is a specialized toolset for deploying AI agents on the Google Cloud Platform with built-in CI/CD, evaluation tools, and observability features. ## Choose when ### Choose agentfield if… - agentfield is primarily Go; agent-starter-pack is Python. - Tags unique to agentfield: agent-auth, agent-authentication, agent-scaling, agentic-ai. - When you seek to manage and scale your AI agents with robust identity awareness and auditability features from inception. ### Choose agent-starter-pack if… - agent-starter-pack is primarily Python; agentfield is Go. - Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks.. - Tags unique to agent-starter-pack: agents, gcp, gemini, genai-agents. - Also covers Inference & Serving, LLM Frameworks. - When you require production-ready templates specifically adapted for deployment to Google Cloud. ## When NOT to use agentfield - If your project requires heavy customization in languages other than Go as Agentfield is primarily built using Go which may limit its adaptability in polyglot environments. ## When NOT to use agent-starter-pack - If you are using another cloud provider (e.g., AWS, Azure) and do not plan on moving your operations to Google Cloud. - When your team lacks familiarity with Python 3.10+ or does not wish to install and manage dependencies such as the Google Cloud SDK locally. ## Common questions ### What is the difference between agentfield and agent-starter-pack? agentfield: Build, run and scale AI agents like API and microservices. agent-starter-pack: Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentfield over agent-starter-pack? Choose agentfield over agent-starter-pack when agentfield is primarily Go; agent-starter-pack is Python; Tags unique to agentfield: agent-auth, agent-authentication, agent-scaling, agentic-ai; When you seek to manage and scale your AI agents with robust identity awareness and auditability features from inception. ### When should I choose agent-starter-pack over agentfield? Choose agent-starter-pack over agentfield when agent-starter-pack is primarily Python; agentfield is Go; Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks.; Tags unique to agent-starter-pack: agents, gcp, gemini, genai-agents; Also covers Inference & Serving, LLM Frameworks; When you require production-ready templates specifically adapted for deployment to Google Cloud. ### When should I avoid agentfield? If your project requires heavy customization in languages other than Go as Agentfield is primarily built using Go which may limit its adaptability in polyglot environments. ### When should I avoid agent-starter-pack? If you are using another cloud provider (e.g., AWS, Azure) and do not plan on moving your operations to Google Cloud. When your team lacks familiarity with Python 3.10+ or does not wish to install and manage dependencies such as the Google Cloud SDK locally. ### Is agentfield or agent-starter-pack more popular on GitHub? agent-starter-pack has more GitHub stars (6,514 vs 2,339). Stars measure visibility, not whether either tool fits your constraints. ### Are agentfield and agent-starter-pack open source? Yes - both are open-source projects on GitHub (agentfield: Apache-2.0, agent-starter-pack: Apache-2.0). ### Where can I find alternatives to agentfield or agent-starter-pack? GraphCanon lists graph-backed alternatives at [agentfield alternatives](/tools/agent-field-agentfield/alternatives) and [agent-starter-pack alternatives](/tools/googlecloudplatform-agent-starter-pack/alternatives) ([agentfield markdown twin](/tools/agent-field-agentfield/alternatives.md), [agent-starter-pack markdown twin](/tools/googlecloudplatform-agent-starter-pack/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/agent-field-agentfield-vs-googlecloudplatform-agent-starter-pack.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentfield or agent-starter-pack? agentfield: Very active. agent-starter-pack: 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 agentfield and agent-starter-pack? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentfield trust report](/tools/agent-field-agentfield/trust); [agent-starter-pack trust report](/tools/googlecloudplatform-agent-starter-pack/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agent-field-agentfield`](/api/graphcanon/graph?tool=agent-field-agentfield) - 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/_