Comparison
agenta vs agentdojo
Verdict
Pick agenta if agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L; pick agentdojo if agentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
Markdown twin · agenta alternatives · agentdojo alternatives
GraphCanon updated today
Trust & integrity
| Signal | agenta | agentdojo |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Steady (39d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- agenta
- The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.
- agentdojo
- A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
Stars
- agenta
- 4.3k
- agentdojo
- 659
Forks
- agenta
- 565
- agentdojo
- 168
Open issues
- agenta
- 184
- agentdojo
- 33
Language
- agenta
- TypeScript
- agentdojo
- Python
Adopt for
- agenta
- Agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L
- agentdojo
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
Persona
- agenta
- -
- agentdojo
- -
Runtime
- agenta
- -
- agentdojo
- -
License
- agenta
- Other
- agentdojo
- MIT
Last pushed
- agenta
- Jul 11, 2026
- agentdojo
- Jun 2, 2026
Categories
- agenta
- AI Agents, LLM Frameworks, Inference & Serving
- agentdojo
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agenta
- Very active (96%)
- agentdojo
- Steady (60%)
Days since push
- agenta
- 0d
- agentdojo
- 39d
Open issues (now)
- agenta
- 184
- agentdojo
- 33
Full report
- agenta
- Trust report
- agentdojo
- Trust report
Choose agenta if…
- agenta is primarily TypeScript; agentdojo is Python.
- License: agenta is Other, agentdojo is MIT.
- Tags unique to agenta: llm-framework, llm-monitoring, evaluation, agents.
- Also covers LLM Frameworks, Inference & Serving.
- You should use Agenta if you're working on managing prompts and evaluating the performance of your language models while needing observability features in an open-source environment.
When NOT to use agenta
- Avoid Agenta if you prefer pre-packaged SaaS solutions over DIY open-source deployments; setting up and maintaining can be complex.
- Agenta may not be suitable if your project or organization does not have the technical know-how to handle self-hosted environments, as configuration and deployment require specific Docker setup.
Choose agentdojo if…
- agentdojo is primarily Python; agenta is TypeScript.
- License: agentdojo is MIT, agenta is Other.
- Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs..
- Requirements: Min 8 GB RAM.
- Tags unique to agentdojo: prompt-injection, benchmark, large-language-models, security.
- Also covers Evaluation & Observability.
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
When NOT to use agentdojo
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Agenta-AI/agenta) · observed Jul 11, 2026
- GitHub forks (Agenta-AI/agenta) · observed Jul 11, 2026
- Last push (Agenta-AI/agenta) · observed Jul 11, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ethz-spylab/agentdojo) · observed Jul 11, 2026
- GitHub forks (ethz-spylab/agentdojo) · observed Jul 11, 2026
- Last push (ethz-spylab/agentdojo) · observed Jun 2, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agenta 4.3k · agentdojo 659 (synced Jul 11, 2026).
Common questions
- What is the difference between agenta and agentdojo?
- agenta: The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.. agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose agenta over agentdojo?
- Choose agenta over agentdojo when agenta is primarily TypeScript; agentdojo is Python; License: agenta is Other, agentdojo is MIT; Tags unique to agenta: llm-framework, llm-monitoring, evaluation, agents; Also covers LLM Frameworks, Inference & Serving; You should use Agenta if you're working on managing prompts and evaluating the performance of your language models while needing observability features in an open-source environment.
- When should I choose agentdojo over agenta?
- Choose agentdojo over agenta when agentdojo is primarily Python; agenta is TypeScript; License: agentdojo is MIT, agenta is Other; Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs.; Requirements: Min 8 GB RAM; Tags unique to agentdojo: prompt-injection, benchmark, large-language-models, security; Also covers Evaluation & Observability; AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- When should I avoid agenta?
- Avoid Agenta if you prefer pre-packaged SaaS solutions over DIY open-source deployments; setting up and maintaining can be complex. Agenta may not be suitable if your project or organization does not have the technical know-how to handle self-hosted environments, as configuration and deployment require specific Docker setup.
- When should I avoid agentdojo?
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- Is agenta or agentdojo more popular on GitHub?
- agenta has more GitHub stars (4,283 vs 659). Stars measure visibility, not whether either tool fits your constraints.
- Are agenta and agentdojo open source?
- Yes - both are open-source projects on GitHub (agenta: Other, agentdojo: MIT).
- Where can I find alternatives to agenta or agentdojo?
- GraphCanon lists graph-backed alternatives at agenta alternatives and agentdojo alternatives (agenta markdown twin, agentdojo 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, agenta or agentdojo?
- agenta: Very active. agentdojo: Steady. 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 agenta and agentdojo?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agenta trust report; agentdojo trust report.