--- title: "agent-starter-pack vs magentic" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/googlecloudplatform-agent-starter-pack-vs-jackmpcollins-magentic" tools: ["googlecloudplatform-agent-starter-pack", "jackmpcollins-magentic"] --- # agent-starter-pack vs magentic *GraphCanon updated Jul 12, 2026* ## Verdict Pick agent-starter-pack when license: agent-starter-pack is Apache-2.0, magentic is MIT; pick magentic when license: magentic is MIT, agent-starter-pack is Apache-2.0. [agent-starter-pack](http://goo.gle/agents-cli) reports 6.5k GitHub stars, 1.5k forks, and 48 open issues, last pushed Jul 10, 2026. [magentic](https://magentic.dev/) has 2.4k stars, 127 forks, and 49 open issues, last pushed Mar 11, 2026. Figures are from public GitHub metadata via [agent-starter-pack's repository](https://github.com/GoogleCloudPlatform/agent-starter-pack) and [magentic's repository](https://github.com/jackmpcollins/magentic). | | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | [magentic](/tools/jackmpcollins-magentic.md) | | --- | --- | --- | | Tagline | Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability. | Seamlessly integrate LLMs as Python functions | | Stars | 6,514 | 2,412 | | Forks | 1,496 | 127 | | Open issues | 48 | 49 | | Language | Python | Python | | 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. | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, AI Agents, Inference & Serving | LLM Frameworks, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | [magentic](/tools/jackmpcollins-magentic.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 121d | | Open issues (now) | 48 | 49 | | Owner type | Organization | User | | Full report | [trust report](/tools/googlecloudplatform-agent-starter-pack/trust.md) | [trust report](/tools/jackmpcollins-magentic/trust.md) | ## Shared compatibility - **Python**: [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) - Python runtime; [magentic](/tools/jackmpcollins-magentic.md) - Python runtime ## 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 agent-starter-pack if… - License: agent-starter-pack is Apache-2.0, magentic is MIT. - Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks.. - Tags unique to agent-starter-pack: llmops, agents, gemini, observability. - Also covers Inference & Serving. - When you require production-ready templates specifically adapted for deployment to Google Cloud. ### Choose magentic if… - License: magentic is MIT, agent-starter-pack is Apache-2.0. - Tags unique to magentic: llm, ai, magenta, chatgpt. ## 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. ## When NOT to use magentic - Last GitHub push was 122 days ago (slowing maintenance, Mar 11, 2026). Validate activity before betting a new project on magentic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ## Common questions ### What is the difference between agent-starter-pack and magentic? agent-starter-pack: Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.. magentic: Seamlessly integrate LLMs as Python functions. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-starter-pack over magentic? Choose agent-starter-pack over magentic when License: agent-starter-pack is Apache-2.0, magentic is MIT; Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks.; Tags unique to agent-starter-pack: llmops, agents, gemini, observability; Also covers Inference & Serving; When you require production-ready templates specifically adapted for deployment to Google Cloud. ### When should I choose magentic over agent-starter-pack? Choose magentic over agent-starter-pack when License: magentic is MIT, agent-starter-pack is Apache-2.0; Tags unique to magentic: llm, ai, magenta, chatgpt. ### 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. ### When should I avoid magentic? Last GitHub push was 122 days ago (slowing maintenance, Mar 11, 2026). Validate activity before betting a new project on magentic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ### Is agent-starter-pack or magentic more popular on GitHub? agent-starter-pack has more GitHub stars (6,514 vs 2,412). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-starter-pack and magentic open source? Yes - both are open-source projects on GitHub (agent-starter-pack: Apache-2.0, magentic: MIT). ### Where can I find alternatives to agent-starter-pack or magentic? GraphCanon lists graph-backed alternatives at [agent-starter-pack alternatives](/tools/googlecloudplatform-agent-starter-pack/alternatives) and [magentic alternatives](/tools/jackmpcollins-magentic/alternatives) ([agent-starter-pack markdown twin](/tools/googlecloudplatform-agent-starter-pack/alternatives.md), [magentic markdown twin](/tools/jackmpcollins-magentic/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/googlecloudplatform-agent-starter-pack-vs-jackmpcollins-magentic.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-starter-pack or magentic? agent-starter-pack: Very active. magentic: Slowing. 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-starter-pack and magentic? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-starter-pack trust report](/tools/googlecloudplatform-agent-starter-pack/trust); [magentic trust report](/tools/jackmpcollins-magentic/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=googlecloudplatform-agent-starter-pack`](/api/graphcanon/graph?tool=googlecloudplatform-agent-starter-pack) - 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/_