Home/Compare/LLFn vs Agent-Reach

Comparison

LLFn vs Agent-Reach

Verdict

Pick LLFn when tags unique to LLFn: python; pick Agent-Reach when tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.

Markdown twin · LLFn alternatives · Agent-Reach alternatives

GraphCanon updated today

LLFn logo

LLFn

orgexyz/LLFn

96pushed Jul 30, 2023
vs
Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

55kpushed Jul 10, 2026

Trust & integrity

SignalLLFnAgent-Reach
Maintenance
Dormant (1076d 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)
No lockfile
As of today · none
No MCP manifest
As of today · mcp_manifest

Tagline

LLFn
A light-weight framework for creating applications using LLMs
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

LLFn
96
Agent-Reach
55k

Forks

LLFn
7
Agent-Reach
4.5k

Open issues

LLFn
1
Agent-Reach
144

Language

LLFn
Python
Agent-Reach
Python

Adopt for

LLFn
-
Agent-Reach
-

Persona

LLFn
-
Agent-Reach
-

Runtime

LLFn
-
Agent-Reach
-

License

LLFn
MIT
Agent-Reach
MIT

Last pushed

LLFn
Jul 30, 2023
Agent-Reach
Jul 10, 2026

Categories

LLFn
LLM Frameworks
Agent-Reach
LLM Frameworks, AI Agents, Developer Tools

Trust and health

Maintenance

LLFn
Dormant (18%)
Agent-Reach
Very active (96%)

Days since push

LLFn
1076d
Agent-Reach
0d

Open issues (now)

LLFn
1
Agent-Reach
144

Owner type

LLFn
Organization
Agent-Reach
User

Security scan

LLFn
No lockfile
Agent-Reach
No MCP manifest

Full report

Agent-Reach
Trust report

Choose LLFn if…

  • Tags unique to LLFn: python.
  • Leaner open-issue backlog (1).

When NOT to use LLFn

  • Last GitHub push was 1077 days ago (dormant maintenance, Jul 30, 2023). Validate activity before betting a new project on LLFn.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose Agent-Reach if…

  • Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
  • Also covers AI Agents, Developer Tools.
  • More GitHub stars (55k vs 96) - visibility, not fit.

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: LLFn 96 · Agent-Reach 55k (synced Jul 11, 2026).

Common questions

What is the difference between LLFn and Agent-Reach?
LLFn: A light-weight framework for creating applications using LLMs. 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 LLFn over Agent-Reach?
Choose LLFn over Agent-Reach when Tags unique to LLFn: python; Leaner open-issue backlog (1).
When should I choose Agent-Reach over LLFn?
Choose Agent-Reach over LLFn when Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools; More GitHub stars (55k vs 96) - visibility, not fit.
When should I avoid LLFn?
Last GitHub push was 1077 days ago (dormant maintenance, Jul 30, 2023). Validate activity before betting a new project on LLFn. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
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 LLFn or Agent-Reach more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 96). Stars measure visibility, not whether either tool fits your constraints.
Are LLFn and Agent-Reach open source?
Yes - both are open-source projects on GitHub (LLFn: MIT, Agent-Reach: MIT).
Where can I find alternatives to LLFn or Agent-Reach?
GraphCanon lists graph-backed alternatives at LLFn alternatives and Agent-Reach alternatives (LLFn 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, LLFn or Agent-Reach?
LLFn: Dormant. 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 LLFn and Agent-Reach?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLFn trust report; Agent-Reach trust report.