Comparison
forge vs agentflow
Verdict
Pick forge if developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge; pick agentflow if agentflow simplifies the creation of complex workflows for large language models through simple JSON configurations.
Markdown twin · forge alternatives · agentflow alternatives
GraphCanon updated Sep 19, 2026
6views this month
vs
Trust & integrity
| Signal | forge | agentflow |
|---|---|---|
| Maintenance | Active (18d since push) As of Sep 19, 2026 · github_public_v1 | Dormant (1100d since push) As of Aug 16, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 19, 2026 · github_public_v1 | Not a fork · Personal account As of Aug 16, 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
- forge
- A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows
- agentflow
- Complex LLM Workflows from Simple JSON
Stars
- forge
- 2.2k
- agentflow
- 320
Forks
- forge
- 173
- agentflow
- 27
Open issues
- forge
- 3
- agentflow
- 13
Language
- forge
- Python
- agentflow
- Python
Adopt for
- forge
- Developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge.
- agentflow
- Agentflow simplifies the creation of complex workflows for large language models through simple JSON configurations.
Persona
- forge
- -
- agentflow
- -
Runtime
- forge
- -
- agentflow
- -
License
- forge
- MIT
- agentflow
- MIT
Last pushed
- forge
- Sep 1, 2026
- agentflow
- Aug 11, 2023
Categories
- forge
- AI Agents, LLM Frameworks
- agentflow
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- forge
- Active (82%)
- agentflow
- Dormant (18%)
Days since push
- forge
- 18d
- agentflow
- 1100d
Open issues (now)
- forge
- 3
- agentflow
- 13
Stars delta
- forge
- +31 (30d)
- agentflow
- -1 (30d)
Open issues delta
- forge
- -1 (30d)
- agentflow
- 0 (30d)
Full report
- forge
- Trust report
- agentflow
- Trust report
Shared compatibility
- Python · forge: Python runtime · agentflow: Python runtime
Choose forge if…
- Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case..
- Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework.
- forge ships Docker support for self-hosted deployment.
- - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic.
When NOT to use forge
- - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup.
- - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management.
- - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services.
Choose agentflow if…
- Tags unique to agentflow: json, large-language-models, python, workflow-management.
- When you need to rapidly prototype LLM workflows with minimal coding via JSON configs
When NOT to use agentflow
- Avoid if requiring advanced customization that goes beyond basic JSON configurations
- Not suitable for scenarios needing real-time dynamic changes in workflow setup during execution
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (antoinezambelli/forge) · observed Sep 19, 2026
- GitHub forks (antoinezambelli/forge) · observed Sep 19, 2026
- Last push (antoinezambelli/forge) · observed Sep 1, 2026
- License file (MIT) · observed Sep 19, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (simonmesmith/agentflow) · observed Sep 19, 2026
- GitHub forks (simonmesmith/agentflow) · observed Sep 19, 2026
- Last push (simonmesmith/agentflow) · observed Aug 11, 2023
- License file (MIT) · observed Sep 19, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: forge 2.2k · agentflow 320 (synced Sep 19, 2026).
Common questions
- What is the difference between forge and agentflow?
- forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. agentflow: Complex LLM Workflows from Simple JSON. See the comparison table for live GitHub stats and shared categories.
- When should I choose forge over agentflow?
- Choose forge over agentflow when Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case.; Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework; forge ships Docker support for self-hosted deployment; - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic.
- When should I choose agentflow over forge?
- Choose agentflow over forge when Tags unique to agentflow: json, large-language-models, python, workflow-management; When you need to rapidly prototype LLM workflows with minimal coding via JSON configs.
- When should I avoid forge?
- - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup. - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management. - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services.
- When should I avoid agentflow?
- Avoid if requiring advanced customization that goes beyond basic JSON configurations Not suitable for scenarios needing real-time dynamic changes in workflow setup during execution
- Is forge or agentflow more popular on GitHub?
- forge has more GitHub stars (2,248 vs 320). Stars measure visibility, not whether either tool fits your constraints.
- Are forge and agentflow open source?
- Yes - both are open-source projects on GitHub (forge: MIT, agentflow: MIT).
- Where can I find alternatives to forge or agentflow?
- GraphCanon lists graph-backed alternatives at forge alternatives and agentflow alternatives (forge markdown twin, agentflow 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, forge or agentflow?
- forge: Active. agentflow: Dormant. 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 forge and agentflow?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: forge trust report; agentflow trust report.