Comparison
agent-control vs agency
Verdict
Pick agent-control if agent-control is a centralized control plane for managing the runtime behavior of AI agents, offering configurability and extensibility for production environments; pick agency if agency is a fast and minimal Python-based framework for developing agentic systems that excels in its streamlined approach to creating autonomous agents.
Markdown twin · agent-control alternatives · agency alternatives
GraphCanon updated Sep 30, 2026
11views this month
vs
Trust & integrity
| Signal | agent-control | agency |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 11, 2026 · github_public_v1 | Slowing (101d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 11, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- agency
- A fast and minimal framework for building agentic systems
Stars
- agent-control
- 305
- agency
- 490
Forks
- agent-control
- 51
- agency
- 29
Open issues
- agent-control
- 36
- agency
- 19
Language
- agent-control
- Python
- agency
- Python
Adopt for
- agent-control
- agent-control is a centralized control plane for managing the runtime behavior of AI agents, offering configurability and extensibility for production environments.
- agency
- Agency is a fast and minimal Python-based framework for developing agentic systems that excels in its streamlined approach to creating autonomous agents.
Persona
- agent-control
- -
- agency
- -
Runtime
- agent-control
- -
- agency
- -
License
- agent-control
- Apache-2.0
- agency
- MIT
Last pushed
- agent-control
- Sep 9, 2026
- agency
- Jun 10, 2026
Categories
- agent-control
- AI Agents
- agency
- AI Agents
Trust and health
Maintenance
- agent-control
- Very active (96%)
- agency
- Slowing (36%)
Days since push
- agent-control
- 1d
- agency
- 101d
Open issues (now)
- agent-control
- 36
- agency
- 19
Stars delta
- agent-control
- +16 (30d)
- agency
- +3 (30d)
Owner type
- agent-control
- Organization
- agency
- User
Full report
- agent-control
- Trust report
- agency
- Trust report
Shared compatibility
- Python · agent-control: Python runtime · agency: Python runtime
Choose agent-control if…
- License: agent-control is Apache-2.0, agency is MIT.
- Pricing: The tool is free to use under the Apache-2.0 license, but additional services or support may incur costs..
- Requirements: Min 2 GB RAM; Requires Docker; Requires Python 3.12+ and Docker or Podman for setup..
- Tags unique to agent-control: agentic-workflow, ai-safety, docker, guardrails.
- agent-control ships Docker support for self-hosted deployment.
- When you need a centralized system to govern the runtime behavior of multiple AI agents at scale.
When NOT to use agent-control
- If your project does not require centralized control over multiple agents and can manage agent behavior independently.
- If you are working with Python versions lower than 3.12 and cannot upgrade your environment.
- When you prefer not to use Docker or Podman for setting up the control plane.
- If your project does not need the flexibility of creating controls via a UI or SDK/API and can function with more rigid configurations.
Choose agency if…
- License: agency is MIT, agent-control is Apache-2.0.
- Tags unique to agency: actor-model, agent-framework, autonomous-agents.
- When you prefer a lightweight solution for building autonomous agent systems without the need for extensive configuration or complex dependencies.
When NOT to use agency
- If your development requires deeply integrated functionalities that would necessitate a heavier, more feature-rich framework.
- In scenarios where you need robust tooling for large-scale deployment and management as Agency does not offer extensive LLMOps (LLM Operations) capabilities beyond its minimalistic design.
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 Sep 30, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (operand/agency) · observed Sep 20, 2026
- GitHub forks (operand/agency) · observed Sep 20, 2026
- Last push (operand/agency) · observed Jun 10, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agent-control 305 · agency 490 (synced Sep 20, 2026).
Common questions
- What is the difference between agent-control and agency?
- agent-control: Centralized agent control plane for governing runtime agent behavior at scale. agency: A fast and minimal framework for building agentic systems. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-control over agency?
- Choose agent-control over agency when License: agent-control is Apache-2.0, agency is MIT; Pricing: The tool is free to use under the Apache-2.0 license, but additional services or support may incur costs.; Requirements: Min 2 GB RAM; Requires Docker; Requires Python 3.12+ and Docker or Podman for setup.; Tags unique to agent-control: agentic-workflow, ai-safety, docker, guardrails; agent-control ships Docker support for self-hosted deployment; When you need a centralized system to govern the runtime behavior of multiple AI agents at scale.
- When should I choose agency over agent-control?
- Choose agency over agent-control when License: agency is MIT, agent-control is Apache-2.0; Tags unique to agency: actor-model, agent-framework, autonomous-agents; When you prefer a lightweight solution for building autonomous agent systems without the need for extensive configuration or complex dependencies.
- When should I avoid agent-control?
- If your project does not require centralized control over multiple agents and can manage agent behavior independently. If you are working with Python versions lower than 3.12 and cannot upgrade your environment. When you prefer not to use Docker or Podman for setting up the control plane. If your project does not need the flexibility of creating controls via a UI or SDK/API and can function with more rigid configurations.
- When should I avoid agency?
- If your development requires deeply integrated functionalities that would necessitate a heavier, more feature-rich framework. In scenarios where you need robust tooling for large-scale deployment and management as Agency does not offer extensive LLMOps (LLM Operations) capabilities beyond its minimalistic design.
- Is agent-control or agency more popular on GitHub?
- agency has more GitHub stars (490 vs 305). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-control and agency open source?
- Yes - both are open-source projects on GitHub (agent-control: Apache-2.0, agency: MIT).
- Where can I find alternatives to agent-control or agency?
- GraphCanon lists graph-backed alternatives at agent-control alternatives and agency alternatives (agent-control markdown twin, agency 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 agency?
- agent-control: Very active. agency: 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-control and agency?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-control trust report; agency trust report.