Home/Compare/garak vs Agent-Reach

Comparison

garak vs Agent-Reach

Verdict

Pick garak when license: garak is Apache-2.0, Agent-Reach is MIT; pick Agent-Reach when license: Agent-Reach is MIT, garak is Apache-2.0.

Markdown twin · garak alternatives · Agent-Reach alternatives

GraphCanon updated today

garak logo

garak

NVIDIA/garak

8.4kpushed Jul 10, 2026
vs
Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

55kpushed Jul 10, 2026

Trust & integrity

SignalgarakAgent-Reach
Maintenance
Very active (1d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
54 low (54 low)
As of today · osv@v1
No MCP manifest
As of today · mcp_manifest

Tagline

garak
the LLM vulnerability scanner
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.

Stars

garak
8.4k
Agent-Reach
55k

Forks

garak
1.1k
Agent-Reach
4.5k

Open issues

garak
367
Agent-Reach
144

Language

garak
Python
Agent-Reach
Python

Adopt for

garak
-
Agent-Reach
-

Persona

garak
-
Agent-Reach
-

Runtime

garak
-
Agent-Reach
-

License

garak
Apache-2.0
Agent-Reach
MIT

Last pushed

garak
Jul 10, 2026
Agent-Reach
Jul 10, 2026

Categories

garak
Vector Databases, LLM Frameworks, Evaluation & Observability
Agent-Reach
LLM Frameworks, AI Agents, Developer Tools

Trust and health

Days since push

garak
1d
Agent-Reach
0d

Open issues (now)

garak
367
Agent-Reach
144

Owner type

garak
Organization
Agent-Reach
User

Security scan

garak
54 low (54 low)
Agent-Reach
No MCP manifest

Full report

Agent-Reach
Trust report

Choose garak if…

  • License: garak is Apache-2.0, Agent-Reach is MIT.
  • Tags unique to garak: ai, python, security-scanners, llm-security.
  • Also covers Vector Databases, Evaluation & Observability.

When NOT to use garak

  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.

Choose Agent-Reach if…

  • License: Agent-Reach is MIT, garak is Apache-2.0.
  • Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
  • Also covers AI Agents, Developer Tools.

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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: garak 8.4k · Agent-Reach 55k (synced Jul 11, 2026).

Common questions

What is the difference between garak and Agent-Reach?
garak: the LLM vulnerability scanner. 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.. See the comparison table for live GitHub stats and shared categories.
When should I choose garak over Agent-Reach?
Choose garak over Agent-Reach when License: garak is Apache-2.0, Agent-Reach is MIT; Tags unique to garak: ai, python, security-scanners, llm-security; Also covers Vector Databases, Evaluation & Observability.
When should I choose Agent-Reach over garak?
Choose Agent-Reach over garak when License: Agent-Reach is MIT, garak is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools.
When should I avoid garak?
Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
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.
Is garak or Agent-Reach more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 8,400). Stars measure visibility, not whether either tool fits your constraints.
Are garak and Agent-Reach open source?
Yes - both are open-source projects on GitHub (garak: Apache-2.0, Agent-Reach: MIT).
Where can I find alternatives to garak or Agent-Reach?
GraphCanon lists graph-backed alternatives at garak alternatives and Agent-Reach alternatives (garak markdown twin, Agent-Reach 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, garak or Agent-Reach?
garak: Very active. Agent-Reach: Very active. 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 garak and Agent-Reach?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: garak trust report; Agent-Reach trust report.