Comparison
agent-starter-pack vs mcp-agent
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.
Markdown twin · agent-starter-pack alternatives · mcp-agent alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | agent-starter-pack | mcp-agent |
|---|---|---|
| Maintenance | Active (29d since push) As of 4d · github_public_v1 | Slowing (181d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Organization account As of 4w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- 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.
Stars
- agent-starter-pack
- 6.5k
- mcp-agent
- 8.5k
Forks
- agent-starter-pack
- 1.5k
- mcp-agent
- 866
Open issues
- agent-starter-pack
- 49
- mcp-agent
- 140
Language
- agent-starter-pack
- Python
- mcp-agent
- Python
Adopt for
- agent-starter-pack
- agent-starter-pack offers built-in CI/CD, evaluation tools, and observability for deploying generative AI agents on Google Cloud with Python.
- mcp-agent
- Allows creation of efficient AI agents via Model Context Protocol with workflow patterns
Persona
- agent-starter-pack
- -
- mcp-agent
- -
Runtime
- agent-starter-pack
- -
- mcp-agent
- -
License
- agent-starter-pack
- Apache-2.0
- mcp-agent
- Apache-2.0
Last pushed
- agent-starter-pack
- Jul 21, 2026
- mcp-agent
- Jan 25, 2026
Categories
- agent-starter-pack
- AI Agents, Evaluation & Observability
- mcp-agent
- AI Agents
Trust and health
Maintenance
- agent-starter-pack
- Active (82%)
- mcp-agent
- Slowing (36%)
Days since push
- agent-starter-pack
- 29d
- mcp-agent
- 181d
Open issues (now)
- agent-starter-pack
- 49
- mcp-agent
- 140
Stars delta
- agent-starter-pack
- +18 (30d)
- mcp-agent
- Unknown
Open issues delta
- agent-starter-pack
- +1 (30d)
- mcp-agent
- Unknown
Full report
- agent-starter-pack
- Trust report
- mcp-agent
- Trust report
Shared compatibility
- Python · agent-starter-pack: Python runtime · mcp-agent: Python runtime
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.
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.
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 mcp-agent
- Require a more customizable approach beyond pre-defined protocol and workflows
- Project demands specific AI frameworks unsupported by Model Context Protocol directly
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (GoogleCloudPlatform/agent-starter-pack) · observed Aug 20, 2026
- GitHub forks (GoogleCloudPlatform/agent-starter-pack) · observed Aug 20, 2026
- Last push (GoogleCloudPlatform/agent-starter-pack) · observed Jul 21, 2026
- License file (Apache-2.0) · observed Aug 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (lastmile-ai/mcp-agent) · observed Jul 26, 2026
- GitHub forks (lastmile-ai/mcp-agent) · observed Jul 26, 2026
- Last push (lastmile-ai/mcp-agent) · observed Jan 25, 2026
- License file (Apache-2.0) · observed Jul 26, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-starter-pack 6.5k · mcp-agent 8.5k (synced Aug 20, 2026).
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 (8,478 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 and mcp-agent alternatives (agent-starter-pack markdown twin, mcp-agent markdown twin), 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 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; mcp-agent trust report.