Comparison
agentfield vs agency
Verdict
Pick agentfield if agentfield is a repository for developing and managing AI agents with a focus on scalability and cloud-native deployment, supporting multiple programming languages including Go, Python, and TypeScript; 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 · agentfield alternatives · agency alternatives
GraphCanon updated Sep 30, 2026
9views this month
vs
Trust & integrity
| Signal | agentfield | agency |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 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 18, 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 Sep 18, 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
- agentfield
- Build, run and scale AI agents like API and microservices
- agency
- A fast and minimal framework for building agentic systems
Stars
- agentfield
- 2.6k
- agency
- 490
Forks
- agentfield
- 415
- agency
- 29
Open issues
- agentfield
- 45
- agency
- 19
Language
- agentfield
- Go
- agency
- Python
Adopt for
- agentfield
- Agentfield is a repository for developing and managing AI agents with a focus on scalability and cloud-native deployment, supporting multiple programming languages including Go, Python, and TypeScript.
- 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
- agentfield
- -
- agency
- -
Runtime
- agentfield
- -
- agency
- -
License
- agentfield
- Apache-2.0
- agency
- MIT
Last pushed
- agentfield
- Sep 17, 2026
- agency
- Jun 10, 2026
Categories
- agentfield
- AI Agents, Inference & Serving
- agency
- AI Agents
Trust and health
Maintenance
- agentfield
- Very active (96%)
- agency
- Slowing (36%)
Days since push
- agentfield
- 0d
- agency
- 101d
Open issues (now)
- agentfield
- 45
- agency
- 19
Stars delta
- agentfield
- +93 (30d)
- agency
- +3 (30d)
Open issues delta
- agentfield
- -29 (30d)
- agency
- 0 (30d)
Owner type
- agentfield
- Organization
- agency
- User
Full report
- agentfield
- Trust report
- agency
- Trust report
Choose agentfield if…
- agentfield is primarily Go; agency is Python.
- License: agentfield is Apache-2.0, agency is MIT.
- Tags unique to agentfield: agent, agent-auth, agent-authentication, agent-indentity.
- Also covers Inference & Serving.
- When you need a scalable solution for deploying AI agents that can be managed like APIs and microservices.
When NOT to use agentfield
- If your project does not require cloud-native deployment or Kubernetes support, as Agentfield is optimized for these environments.
- If you are looking for a tool that focuses solely on a single programming language, as Agentfield supports multiple languages and might be overkill for single-language projects.
- When you need a tool that is not primarily designed for AI agents but for a broader range of microservices or APIs, as Agentfield is specialized for AI agents.
Choose agency if…
- agency is primarily Python; agentfield is Go.
- License: agency is MIT, agentfield 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 (Agent-Field/agentfield) · observed Sep 20, 2026
- GitHub forks (Agent-Field/agentfield) · observed Sep 20, 2026
- Last push (Agent-Field/agentfield) · observed Sep 17, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 30, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 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: agentfield 2.6k · agency 490 (synced Sep 20, 2026).
Common questions
- What is the difference between agentfield and agency?
- agentfield: Build, run and scale AI agents like API and microservices. 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 agentfield over agency?
- Choose agentfield over agency when agentfield is primarily Go; agency is Python; License: agentfield is Apache-2.0, agency is MIT; Tags unique to agentfield: agent, agent-auth, agent-authentication, agent-indentity; Also covers Inference & Serving; When you need a scalable solution for deploying AI agents that can be managed like APIs and microservices.
- When should I choose agency over agentfield?
- Choose agency over agentfield when agency is primarily Python; agentfield is Go; License: agency is MIT, agentfield 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 agentfield?
- If your project does not require cloud-native deployment or Kubernetes support, as Agentfield is optimized for these environments. If you are looking for a tool that focuses solely on a single programming language, as Agentfield supports multiple languages and might be overkill for single-language projects. When you need a tool that is not primarily designed for AI agents but for a broader range of microservices or APIs, as Agentfield is specialized for AI agents.
- 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 agentfield or agency more popular on GitHub?
- agentfield has more GitHub stars (2,565 vs 490). Stars measure visibility, not whether either tool fits your constraints.
- Are agentfield and agency open source?
- Yes - both are open-source projects on GitHub (agentfield: Apache-2.0, agency: MIT).
- Where can I find alternatives to agentfield or agency?
- GraphCanon lists graph-backed alternatives at agentfield alternatives and agency alternatives (agentfield 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, agentfield or agency?
- agentfield: 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 agentfield and agency?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentfield trust report; agency trust report.