Home/Compare/Agent-Reach vs llms-tools

Comparison

Agent-Reach vs llms-tools

Verdict

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

Markdown twin · Agent-Reach alternatives · llms-tools alternatives

GraphCanon updated today

Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

55kpushed Jul 10, 2026
vs
llms-tools logo

llms-tools

PetroIvaniuk/llms-tools

319pushed Jun 1, 2026

Trust & integrity

SignalAgent-Reachllms-tools
Maintenance
Very active (0d since push)
As of today · github_public_v1
Steady (39d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Personal 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.
llms-tools
A list of LLMs Tools & Projects

Stars

Agent-Reach
55k
llms-tools
319

Forks

Agent-Reach
4.5k
llms-tools
46

Open issues

Agent-Reach
144
llms-tools
3

Language

Agent-Reach
Python
llms-tools
-

Adopt for

Agent-Reach
-
llms-tools
-

Persona

Agent-Reach
-
llms-tools
-

Runtime

Agent-Reach
-
llms-tools
-

License

Agent-Reach
MIT
llms-tools
Apache-2.0

Last pushed

Agent-Reach
Jul 10, 2026
llms-tools
Jun 1, 2026

Categories

Agent-Reach
LLM Frameworks, AI Agents, Developer Tools
llms-tools
LLM Frameworks, Evaluation & Observability

Trust and health

Maintenance

Agent-Reach
Very active (96%)
llms-tools
Steady (60%)

Days since push

Agent-Reach
0d
llms-tools
39d

Open issues (now)

Agent-Reach
144
llms-tools
3

Security scan

Agent-Reach
No MCP manifest
llms-tools
No lockfile

Full report

Agent-Reach
Trust report
llms-tools
Trust report

Choose Agent-Reach if…

  • License: Agent-Reach is MIT, llms-tools 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.

Choose llms-tools if…

  • License: llms-tools is Apache-2.0, Agent-Reach is MIT.
  • Tags unique to llms-tools: data-science, chat-bot, llm, ai.
  • Also covers Evaluation & Observability.

When NOT to use llms-tools

  • 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.

Explore

Sources

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

GitHub stars on cards: Agent-Reach 55k · llms-tools 319 (synced Jul 11, 2026).

Common questions

What is the difference between Agent-Reach and llms-tools?
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.. llms-tools: A list of LLMs Tools & Projects. See the comparison table for live GitHub stats and shared categories.
When should I choose Agent-Reach over llms-tools?
Choose Agent-Reach over llms-tools when License: Agent-Reach is MIT, llms-tools 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 choose llms-tools over Agent-Reach?
Choose llms-tools over Agent-Reach when License: llms-tools is Apache-2.0, Agent-Reach is MIT; Tags unique to llms-tools: data-science, chat-bot, llm, ai; Also covers Evaluation & Observability.
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 llms-tools?
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.
Is Agent-Reach or llms-tools more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 319). Stars measure visibility, not whether either tool fits your constraints.
Are Agent-Reach and llms-tools open source?
Yes - both are open-source projects on GitHub (Agent-Reach: MIT, llms-tools: Apache-2.0).
Where can I find alternatives to Agent-Reach or llms-tools?
GraphCanon lists graph-backed alternatives at Agent-Reach alternatives and llms-tools alternatives (Agent-Reach markdown twin, llms-tools 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 llms-tools?
Agent-Reach: Very active. llms-tools: Steady. 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 llms-tools?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agent-Reach trust report; llms-tools trust report.