Comparison
Agent-Reach vs AutoGL
Verdict
Pick Agent-Reach when license: Agent-Reach is MIT, AutoGL is Apache-2.0; pick AutoGL when license: AutoGL is Apache-2.0, Agent-Reach is MIT.
Markdown twin · Agent-Reach alternatives · AutoGL alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | Agent-Reach | AutoGL |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Slowing (233d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No MCP manifest As of today · mcp_manifest | No lockfile As of today · none |
Tagline
- Agent-Reach
- Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
- AutoGL
- An autoML framework & toolkit for machine learning on graphs.
Stars
- Agent-Reach
- 55k
- AutoGL
- 1.1k
Forks
- Agent-Reach
- 4.5k
- AutoGL
- 123
Open issues
- Agent-Reach
- 144
- AutoGL
- 20
Language
- Agent-Reach
- Python
- AutoGL
- Python
Adopt for
- Agent-Reach
- -
- AutoGL
- -
Persona
- Agent-Reach
- -
- AutoGL
- -
Runtime
- Agent-Reach
- -
- AutoGL
- -
License
- Agent-Reach
- MIT
- AutoGL
- Apache-2.0
Last pushed
- Agent-Reach
- Jul 10, 2026
- AutoGL
- Nov 20, 2025
Categories
- Agent-Reach
- LLM Frameworks, AI Agents, Developer Tools
- AutoGL
- Model Training, Developer Tools
Trust and health
Maintenance
- Agent-Reach
- Very active (96%)
- AutoGL
- Slowing (36%)
Days since push
- Agent-Reach
- 0d
- AutoGL
- 233d
Open issues (now)
- Agent-Reach
- 144
- AutoGL
- 20
Owner type
- Agent-Reach
- User
- AutoGL
- Organization
Security scan
- Agent-Reach
- No MCP manifest
- AutoGL
- No lockfile
Full report
- Agent-Reach
- Trust report
- AutoGL
- Trust report
Choose Agent-Reach if…
- License: Agent-Reach is MIT, AutoGL is Apache-2.0.
- Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
- Also covers LLM Frameworks, AI Agents.
When NOT to use Agent-Reach
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
Choose AutoGL if…
- License: AutoGL is Apache-2.0, Agent-Reach is MIT.
- Tags unique to AutoGL: automl, hyper-parameter-optimization, neural-architecture-search, deep-learning.
- Also covers Model Training.
When NOT to use AutoGL
- Last GitHub push was 234 days ago (slowing maintenance, Nov 20, 2025). Validate activity before betting a new project on AutoGL.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Panniantong/Agent-Reach) · observed Jul 11, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Jul 11, 2026
- Last push (Panniantong/Agent-Reach) · observed Jul 10, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (THUMNLab/AutoGL) · observed Jul 11, 2026
- GitHub forks (THUMNLab/AutoGL) · observed Jul 11, 2026
- Last push (THUMNLab/AutoGL) · observed Nov 20, 2025
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Agent-Reach 55k · AutoGL 1.1k (synced Jul 11, 2026).
Common questions
- What is the difference between Agent-Reach and AutoGL?
- Agent-Reach: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.. AutoGL: An autoML framework & toolkit for machine learning on graphs.. See the comparison table for live GitHub stats and shared categories.
- When should I choose Agent-Reach over AutoGL?
- Choose Agent-Reach over AutoGL when License: Agent-Reach is MIT, AutoGL is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers LLM Frameworks, AI Agents.
- When should I choose AutoGL over Agent-Reach?
- Choose AutoGL over Agent-Reach when License: AutoGL is Apache-2.0, Agent-Reach is MIT; Tags unique to AutoGL: automl, hyper-parameter-optimization, neural-architecture-search, deep-learning; Also covers Model Training.
- When should I avoid Agent-Reach?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- When should I avoid AutoGL?
- Last GitHub push was 234 days ago (slowing maintenance, Nov 20, 2025). Validate activity before betting a new project on AutoGL. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- Is Agent-Reach or AutoGL more popular on GitHub?
- Agent-Reach has more GitHub stars (54,715 vs 1,135). Stars measure visibility, not whether either tool fits your constraints.
- Are Agent-Reach and AutoGL open source?
- Yes - both are open-source projects on GitHub (Agent-Reach: MIT, AutoGL: Apache-2.0).
- Where can I find alternatives to Agent-Reach or AutoGL?
- GraphCanon lists graph-backed alternatives at Agent-Reach alternatives and AutoGL alternatives (Agent-Reach markdown twin, AutoGL 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-Reach or AutoGL?
- Agent-Reach: Very active. AutoGL: 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-Reach and AutoGL?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agent-Reach trust report; AutoGL trust report.