Home/Compare/agenta vs agentdojo

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

agenta logo

agenta

Agenta-AI/agenta

4.3kpushed Jul 11, 2026
vs
agentdojo logo

agentdojo

ethz-spylab/agentdojo

659pushed Jun 2, 2026

Trust & integrity

Signalagentaagentdojo
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

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 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.