Comparison
agent-control vs continuum
Verdict
Pick agent-control if agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API; pick continuum if continuum is an agent runtime platform by ShyftLabs for building and orchestrating AI agents using Dockerized infrastructure profiles to manage dependencies and environment configurations.
Markdown twin · agent-control alternatives · continuum alternatives
GraphCanon updated Sep 20, 2026
13views this month
vs
Trust & integrity
| Signal | agent-control | continuum |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 11, 2026 · github_public_v1 | Very active (0d since push) As of Sep 11, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 11, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 11, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | Published findings As of Jul 15, 2026 · 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-control
- Centralized agent control plane for governing runtime agent behavior at scale
- continuum
- Agent runtime by ShyftLabs
Stars
- agent-control
- 305
- continuum
- 84
Forks
- agent-control
- 51
- continuum
- 11
Open issues
- agent-control
- 36
- continuum
- 14
Language
- agent-control
- Python
- continuum
- Python
Adopt for
- agent-control
- agent-control is a highly configurable and extensible centralized agent control system that governs runtime behavior of agents at scale via UI or SDK/API.
- continuum
- Continuum is an agent runtime platform by ShyftLabs for building and orchestrating AI agents using Dockerized infrastructure profiles to manage dependencies and environment configurations.
Persona
- agent-control
- -
- continuum
- -
Runtime
- agent-control
- -
- continuum
- -
License
- agent-control
- Apache-2.0
- continuum
- Continuum is available under the Apache License 2.0, allowing for broad usage with attribution required.
Last pushed
- agent-control
- Sep 9, 2026
- continuum
- Sep 10, 2026
Categories
- agent-control
- AI Agents
- continuum
- AI Agents, Evaluation & Observability
Trust and health
Days since push
- agent-control
- 1d
- continuum
- 0d
Open issues (now)
- agent-control
- 36
- continuum
- 14
Stars delta
- agent-control
- +16 (30d)
- continuum
- +5 (30d)
Open issues delta
- agent-control
- 0 (30d)
- continuum
- +2 (30d)
OSV dependency advisories
- agent-control
- No lockfile (source not queried)
- continuum
- Published findings
Full report
- agent-control
- Trust report
- continuum
- Trust report
Shared compatibility
- Python · agent-control: Python runtime · continuum: Python runtime
Choose agent-control if…
- Tags unique to agent-control: agentic-workflow, ai-safety, guardrails, llm.
- Use agent-control if you need to centrally manage the behavior of multiple AI agents in production environments.
- More GitHub stars (305 vs 84) - visibility, not fit.
When NOT to use agent-control
- Avoid using agent-control when your project does not require centralized control for large-scale AI agent management.
- Not recommended if your setup is simplistic or relies solely on languages other than Python or TypeScript, since the tool primarily supports these two.
Choose continuum if…
- Requirements: Requires Docker; Python version 3.13+ required..
- Tags unique to continuum: agent-framework, agentic-ai, ai-agents, llm-framework.
- Also covers Evaluation & Observability.
- Use Continuum when you require fine-grained control over the operational environments of your AI agents through its minimal, standard, or full infrastructure profiles.
When NOT to use continuum
- Avoid using Continuum if you prefer a setup without Docker dependencies for running your AI agents as it heavily relies on Dockerized infrastructure.
- If the specific use case does not need extensive observability or complex runtime configurations, then alternatives with less overhead might be more suitable.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (agentcontrol/agent-control) · observed Sep 20, 2026
- GitHub forks (agentcontrol/agent-control) · observed Sep 20, 2026
- Last push (agentcontrol/agent-control) · observed Sep 9, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (shyftlabs/continuum) · observed Sep 20, 2026
- GitHub forks (shyftlabs/continuum) · observed Sep 20, 2026
- Last push (shyftlabs/continuum) · observed Sep 10, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: agent-control 305 · continuum 84 (synced Sep 20, 2026).
Common questions
- What is the difference between agent-control and continuum?
- agent-control: Centralized agent control plane for governing runtime agent behavior at scale. continuum: Agent runtime by ShyftLabs. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-control over continuum?
- Choose agent-control over continuum when Tags unique to agent-control: agentic-workflow, ai-safety, guardrails, llm; Use agent-control if you need to centrally manage the behavior of multiple AI agents in production environments; More GitHub stars (305 vs 84) - visibility, not fit.
- When should I choose continuum over agent-control?
- Choose continuum over agent-control when Requirements: Requires Docker; Python version 3.13+ required.; Tags unique to continuum: agent-framework, agentic-ai, ai-agents, llm-framework; Also covers Evaluation & Observability; Use Continuum when you require fine-grained control over the operational environments of your AI agents through its minimal, standard, or full infrastructure profiles.
- When should I avoid agent-control?
- Avoid using agent-control when your project does not require centralized control for large-scale AI agent management. Not recommended if your setup is simplistic or relies solely on languages other than Python or TypeScript, since the tool primarily supports these two.
- When should I avoid continuum?
- Avoid using Continuum if you prefer a setup without Docker dependencies for running your AI agents as it heavily relies on Dockerized infrastructure. If the specific use case does not need extensive observability or complex runtime configurations, then alternatives with less overhead might be more suitable.
- Is agent-control or continuum more popular on GitHub?
- agent-control has more GitHub stars (305 vs 84). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-control and continuum open source?
- Yes - both are open-source projects on GitHub (agent-control: Apache-2.0, continuum: Apache-2.0).
- Where can I find alternatives to agent-control or continuum?
- GraphCanon lists graph-backed alternatives at agent-control alternatives and continuum alternatives (agent-control markdown twin, continuum 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-control or continuum?
- agent-control: Very active. continuum: 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-control and continuum?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-control trust report; continuum trust report.