ml-agent-orchestrator
PulseGate's liveness check found it on 14 Sep 2026; it is registered on GitHub and PyPI and has been in the index since 24 Jul 2026. How this is checked
ml-agent-orchestrator is a Python package that provides a closed-loop automated ML experiment engine. It uses Claude Code as an editor and Google Antigravity CLI as an evaluator, with git-based state decisions, persistent agent sessions, context-rotation memory, an AST code graph, and a temporal experiment knowledge graph. It is designed for ML researchers and engineers who want to automate and systematically track their experimentation workflow.
Inferred · not functionally tested
Overview
5 featuresPurpose: Manually managing, tracking, and iterating on machine learning experiments at scale.
Inferred · not functionally tested
Audience: machine learning engineers
Inferred · not functionally tested
Functions: agents, workflow_automation, analytics
Inferred · not functionally tested
Interfaces: API: unknown · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: unknown
Recorded constraints: pricing: open_source · license: MIT · platforms: CLI · deployment: cli
Constraint provenance is unknown; confirm requirements with the publisher.
Record sources: pypi.org · github.com. These links do not verify the individual claims.
ml-agent-orchestrator sits in PulseGate's Frameworks & runtimes category. Inferred · not functionally tested: Manually managing, tracking, and iterating on machine learning experiments at scale. Inferred · not functionally tested: ml-agent-orchestrator is an open-source project aimed at machine learning engineers. Basis unknown · not verified: The project is open source (MIT). Basis unknown · not verified: It runs on the command line.
Behind ml-agent-orchestrator is 1to3for5vi7ate9x, and it first shipped in 2026. Development happens publicly on GitHub with 3 commits in the last 90 days. Inferred · not functionally tested: Key capabilities include closed-loop experimentation, git-based state, and persistent agent sessions.
Summary written by a language model from the project’s public pages.
Tasks: Inferred · not functionally tested
- Closed-loop experimentation
- Git-based state
- Persistent agent sessions
- AST code graph
- Temporal knowledge graph
Topics: Inferred · not functionally tested
Built with & integrations
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
- Indexed24 Jul · 01:38 UTCml-agent-orchestrator seen via PyPI Fresh FeedSource: PyPI Fresh Feed · Open
Frequently asked questions about ml-agent-orchestrator
- What is ml-agent-orchestrator?
- Inferred · not functionally tested: Manually managing, tracking, and iterating on machine learning experiments at scale. It is catalogued under Frameworks & runtimes on PulseGate.
- Who should use ml-agent-orchestrator?
- Inferred · not functionally tested: ml-agent-orchestrator is an open-source project built for machine learning engineers.
- Does ml-agent-orchestrator have a free plan?
- Basis unknown · not verified: Yes — ml-agent-orchestrator is open source under the MIT license and free to use.
- What platforms does ml-agent-orchestrator run on?
- Basis unknown · not verified: ml-agent-orchestrator runs on the command line.
- Is ml-agent-orchestrator still maintained?
- PulseGate's liveness check found it on 14 Sep 2026. Its GitHub repository shows 3 commits in the last 90 days.
- What are alternatives to ml-agent-orchestrator?
- Similar projects tracked by PulseGate include local-ai-agent-orchestrator, ai-agent-orchestrator, and agent-orchestration-process.local-ai-agent-orchestratorai-agent-orchestratoragent-orchestration-process
- Who develops ml-agent-orchestrator?
- ml-agent-orchestrator is developed by 1to3for5vi7ate9x.
- How long has ml-agent-orchestrator been around?
- ml-agent-orchestrator first shipped in 2026.
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