--- title: "agent-starter-pack vs mcp-agent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/googlecloudplatform-agent-starter-pack-vs-lastmile-ai-mcp-agent" tools: ["googlecloudplatform-agent-starter-pack", "lastmile-ai-mcp-agent"] --- # agent-starter-pack vs mcp-agent *GraphCanon updated Aug 26, 2026* ## Verdict Pick agent-starter-pack if agent-starter-pack offers built-in CI/CD, evaluation tools, and observability for deploying generative AI agents on Google Cloud with Python; pick mcp-agent if allows creation of efficient AI agents via Model Context Protocol with workflow patterns. [agent-starter-pack](http://goo.gle/agents-cli) reports 6.5k GitHub stars, 1.5k forks, and 49 open issues, last pushed Jul 21, 2026. [mcp-agent](https://github.com/lastmile-ai/mcp-agent) has 8.5k stars, 879 forks, and 134 open issues, last pushed Jan 25, 2026. Figures are from public GitHub metadata via [agent-starter-pack's repository](https://github.com/GoogleCloudPlatform/agent-starter-pack) and [mcp-agent's repository](https://github.com/lastmile-ai/mcp-agent). | | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | [mcp-agent](/tools/lastmile-ai-mcp-agent.md) | | --- | --- | --- | | Tagline | Ship AI Agents to Google Cloud in minutes with built-in CI/CD, evaluation, and observability | Build effective AI agents with Model Context Protocol. | | Stars | 6,537 | 8,518 | | Forks | 1,502 | 879 | | Open issues | 49 | 134 | | Language | Python | Python | | Adopt for | agent-starter-pack offers built-in CI/CD, evaluation tools, and observability for deploying generative AI agents on Google Cloud with Python. | Allows creation of efficient AI agents via Model Context Protocol with workflow patterns | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | [mcp-agent](/tools/lastmile-ai-mcp-agent.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 29d | 212d | | Open issues (now) | 49 | 134 | | Stars delta | +18 (30d) | +40 (30d) | | Open issues delta | +1 (30d) | -6 (30d) | | Full report | [trust report](/tools/googlecloudplatform-agent-starter-pack/trust.md) | [trust report](/tools/lastmile-ai-mcp-agent/trust.md) | ## Shared compatibility - **Python**: [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) - Python runtime; [mcp-agent](/tools/lastmile-ai-mcp-agent.md) - Python runtime ## Decision facts: agent-starter-pack - **Requirements:** Depends on Python 3.10+.; Requires the Google Cloud SDK for interacting with GCP services.; Terraform is needed for deployment purposes.; Make utility should be installed for development tasks. - **Adopt for:** agent-starter-pack offers built-in CI/CD, evaluation tools, and observability for deploying generative AI agents on Google Cloud with Python. ## Decision facts: mcp-agent - **Adopt for:** Allows creation of efficient AI agents via Model Context Protocol with workflow patterns ## Choose when ### Choose agent-starter-pack if… - Requirements: Depends on Python 3.10+.; Requires the Google Cloud SDK for interacting with GCP services.; Terraform is needed for deployment purposes.; Make utility should be installed for development tasks.. - Tags unique to agent-starter-pack: gcp, gemini, genai-agents, generative-ai. - Also covers Evaluation & Observability. - You are working with Google Cloud and wish to deploy generative AI agents quickly using production-ready templates that come with integrated CI/CD pipelines. ### Choose mcp-agent if… - Tags unique to mcp-agent: ai-agents, llm, mcp, model-context-protocol. - Need to implement the Model Context Protocol specifically in your agent development - More GitHub stars (8.5k vs 6.5k) - visibility, not fit. ## When NOT to use agent-starter-pack - Your project is hosted on a cloud provider other than Google Cloud, as this tool is optimized for GCP services and uses Terraform specifically configured for deployment with it. - You do not need or want built-in CI/CD pipelines and evaluation tools, preferring to manage these components separately through different tools or self-configured setups. ## When NOT to use mcp-agent - Require a more customizable approach beyond pre-defined protocol and workflows - Project demands specific AI frameworks unsupported by Model Context Protocol directly ## Common questions ### What is the difference between agent-starter-pack and mcp-agent? agent-starter-pack: Ship AI Agents to Google Cloud in minutes with built-in CI/CD, evaluation, and observability. mcp-agent: Build effective AI agents with Model Context Protocol.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-starter-pack over mcp-agent? Choose agent-starter-pack over mcp-agent when Requirements: Depends on Python 3.10+.; Requires the Google Cloud SDK for interacting with GCP services.; Terraform is needed for deployment purposes.; Make utility should be installed for development tasks.; Tags unique to agent-starter-pack: gcp, gemini, genai-agents, generative-ai; Also covers Evaluation & Observability; You are working with Google Cloud and wish to deploy generative AI agents quickly using production-ready templates that come with integrated CI/CD pipelines. ### When should I choose mcp-agent over agent-starter-pack? Choose mcp-agent over agent-starter-pack when Tags unique to mcp-agent: ai-agents, llm, mcp, model-context-protocol; Need to implement the Model Context Protocol specifically in your agent development; More GitHub stars (8.5k vs 6.5k) - visibility, not fit. ### When should I avoid agent-starter-pack? Your project is hosted on a cloud provider other than Google Cloud, as this tool is optimized for GCP services and uses Terraform specifically configured for deployment with it. You do not need or want built-in CI/CD pipelines and evaluation tools, preferring to manage these components separately through different tools or self-configured setups. ### When should I avoid mcp-agent? Require a more customizable approach beyond pre-defined protocol and workflows Project demands specific AI frameworks unsupported by Model Context Protocol directly ### Is agent-starter-pack or mcp-agent more popular on GitHub? mcp-agent has more GitHub stars (8,518 vs 6,537). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-starter-pack and mcp-agent open source? Yes - both are open-source projects on GitHub (agent-starter-pack: Apache-2.0, mcp-agent: Apache-2.0). ### Where can I find alternatives to agent-starter-pack or mcp-agent? GraphCanon lists graph-backed alternatives at [agent-starter-pack alternatives](/tools/googlecloudplatform-agent-starter-pack/alternatives) and [mcp-agent alternatives](/tools/lastmile-ai-mcp-agent/alternatives) ([agent-starter-pack markdown twin](/tools/googlecloudplatform-agent-starter-pack/alternatives.md), [mcp-agent markdown twin](/tools/lastmile-ai-mcp-agent/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-lastmile-ai-mcp-agent.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 mcp-agent? agent-starter-pack: Active. mcp-agent: 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 mcp-agent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-starter-pack trust report](/tools/googlecloudplatform-agent-starter-pack/trust); [mcp-agent trust report](/tools/lastmile-ai-mcp-agent/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/_