Comparison
agent-protocol vs LazyLLM
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 LazyLLM if critical facts for LazyLLM.
Markdown twin · agent-protocol alternatives · LazyLLM alternatives
GraphCanon updated 2w · 33 views this month
vs
Trust & integrity
| Signal | agent-protocol | LazyLLM |
|---|---|---|
| Maintenance | Dormant (484d since push) As of 2w · github_public_v1 | Very active (0d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | Published findings 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-protocol
- Common interface for AI agents
- LazyLLM
- Easiest and laziest way for building multi-agent LLMs applications.
Stars
- agent-protocol
- 1.5k
- LazyLLM
- 3.9k
Forks
- agent-protocol
- 185
- LazyLLM
- 404
Open issues
- agent-protocol
- 50
- LazyLLM
- 41
Language
- agent-protocol
- Python
- LazyLLM
- Python
Adopt for
- agent-protocol
- 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.
- LazyLLM
- Critical facts for LazyLLM
Persona
- agent-protocol
- -
- LazyLLM
- -
Runtime
- agent-protocol
- -
- LazyLLM
- -
License
- agent-protocol
- MIT
- LazyLLM
- Apache-2.0
Last pushed
- agent-protocol
- Apr 8, 2025
- LazyLLM
- Aug 7, 2026
Categories
- agent-protocol
- AI Agents
- LazyLLM
- AI Agents, Model Training
Trust and health
Maintenance
- agent-protocol
- Dormant (18%)
- LazyLLM
- Very active (96%)
Days since push
- agent-protocol
- 484d
- LazyLLM
- 0d
Open issues (now)
- agent-protocol
- 50
- LazyLLM
- 41
Full report
- agent-protocol
- Trust report
- LazyLLM
- Trust report
Choose agent-protocol if…
- License: agent-protocol is MIT, LazyLLM is Apache-2.0.
- Tags unique to agent-protocol: api, auto-gpt, gpt-4, javascript.
- When you want to ensure interoperability between different AI agents irrespective of the frameworks used by them.
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.
Choose LazyLLM if…
- License: LazyLLM is Apache-2.0, agent-protocol is MIT.
- Pricing: LazyLLM is open-source under the Apache-2.0 license, making it free to use for both personal and commercial projects..
- Requirements: Min 8 GB RAM; Installation can be done via pip or from source. No Docker required, but a Python environment is necessary..
- Tags unique to LazyLLM: deep-learning, framework, llm, multi-agent.
- Also covers Model Training.
- - When you need a highly user-friendly framework specifically designed for building multi-agent LLM applications, emphasizing simplicity and streamlined installation.
When NOT to use LazyLLM
- - Avoid if you require extensive customization options or a more complex framework; LazyLLM's focus on being the 'laziest' way may mean it lacks advanced or specialized features found in other tools.
- - If you are working with non-Python environments, as LazyLLM is specifically language-oriented towards Python. Users needing cross-language support might not find LazyLLM suitable.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (agi-inc/agent-protocol) · observed Aug 6, 2026
- GitHub forks (agi-inc/agent-protocol) · observed Aug 6, 2026
- Last push (agi-inc/agent-protocol) · observed Apr 8, 2025
- License file (MIT) · observed Aug 6, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (LazyAGI/LazyLLM) · observed Aug 8, 2026
- GitHub forks (LazyAGI/LazyLLM) · observed Aug 8, 2026
- Last push (LazyAGI/LazyLLM) · observed Aug 7, 2026
- License file (Apache-2.0) · observed Aug 8, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-protocol 1.5k · LazyLLM 3.9k (synced Aug 6, 2026).
Common questions
- What is the difference between agent-protocol and LazyLLM?
- agent-protocol: Common interface for AI agents. LazyLLM: Easiest and laziest way for building multi-agent LLMs applications.. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-protocol over LazyLLM?
- Choose agent-protocol over LazyLLM when License: agent-protocol is MIT, LazyLLM is Apache-2.0; Tags unique to agent-protocol: api, auto-gpt, gpt-4, javascript; When you want to ensure interoperability between different AI agents irrespective of the frameworks used by them.
- When should I choose LazyLLM over agent-protocol?
- Choose LazyLLM over agent-protocol when License: LazyLLM is Apache-2.0, agent-protocol is MIT; Pricing: LazyLLM is open-source under the Apache-2.0 license, making it free to use for both personal and commercial projects.; Requirements: Min 8 GB RAM; Installation can be done via pip or from source. No Docker required, but a Python environment is necessary.; Tags unique to LazyLLM: deep-learning, framework, llm, multi-agent; Also covers Model Training; - When you need a highly user-friendly framework specifically designed for building multi-agent LLM applications, emphasizing simplicity and streamlined installation.
- 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 LazyLLM?
- - Avoid if you require extensive customization options or a more complex framework; LazyLLM's focus on being the 'laziest' way may mean it lacks advanced or specialized features found in other tools. - If you are working with non-Python environments, as LazyLLM is specifically language-oriented towards Python. Users needing cross-language support might not find LazyLLM suitable.
- Is agent-protocol or LazyLLM more popular on GitHub?
- LazyLLM has more GitHub stars (3,866 vs 1,458). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-protocol and LazyLLM open source?
- Yes - both are open-source projects on GitHub (agent-protocol: MIT, LazyLLM: Apache-2.0).
- Where can I find alternatives to agent-protocol or LazyLLM?
- GraphCanon lists graph-backed alternatives at agent-protocol alternatives and LazyLLM alternatives (agent-protocol markdown twin, LazyLLM 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-protocol or LazyLLM?
- agent-protocol: Dormant. LazyLLM: 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 LazyLLM?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-protocol trust report; LazyLLM trust report.