Home/Compare/parlor vs Agent-Reach

Comparison

parlor vs Agent-Reach

Verdict

Pick parlor when parlor is primarily HTML; Agent-Reach is Python; pick Agent-Reach when agent-Reach is primarily Python; parlor is HTML.

Markdown twin · parlor alternatives · Agent-Reach alternatives

GraphCanon updated today

parlor logo

parlor

fikrikarim/parlor

1.9kpushed Jul 11, 2026
vs
Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

55kpushed Jul 10, 2026

Trust & integrity

SignalparlorAgent-Reach
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (0d 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 lockfile
As of today · none
No MCP manifest
As of today · mcp_manifest

Tagline

parlor
On-device, real-time multimodal AI. Have natural voice and vision conversations with an AI that runs entirely on your machine. Powered by Gemma 4 E2B and Kokoro.
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

parlor
1.9k
Agent-Reach
55k

Forks

parlor
240
Agent-Reach
4.5k

Open issues

parlor
7
Agent-Reach
144

Language

parlor
HTML
Agent-Reach
Python

Adopt for

parlor
-
Agent-Reach
-

Persona

parlor
-
Agent-Reach
-

Runtime

parlor
-
Agent-Reach
-

License

parlor
Apache-2.0
Agent-Reach
MIT

Last pushed

parlor
Jul 11, 2026
Agent-Reach
Jul 10, 2026

Categories

parlor
LLM Frameworks, Speech & Audio, Computer Vision
Agent-Reach
AI Agents, LLM Frameworks, Developer Tools

Trust and health

Open issues (now)

parlor
7
Agent-Reach
144

Security scan

parlor
No lockfile
Agent-Reach
No MCP manifest

Full report

Agent-Reach
Trust report

Choose parlor if…

  • parlor is primarily HTML; Agent-Reach is Python.
  • License: parlor is Apache-2.0, Agent-Reach is MIT.
  • Tags unique to parlor: gemma, litert-lm, kokoro, on-device-ai.
  • Also covers Speech & Audio, Computer Vision.

When NOT to use parlor

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose Agent-Reach if…

  • Agent-Reach is primarily Python; parlor is HTML.
  • License: Agent-Reach is MIT, parlor 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

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • 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: parlor 1.9k · Agent-Reach 55k (synced Jul 11, 2026).

Common questions

What is the difference between parlor and Agent-Reach?
parlor: On-device, real-time multimodal AI. Have natural voice and vision conversations with an AI that runs entirely on your machine. Powered by Gemma 4 E2B and Kokoro.. 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 parlor over Agent-Reach?
Choose parlor over Agent-Reach when parlor is primarily HTML; Agent-Reach is Python; License: parlor is Apache-2.0, Agent-Reach is MIT; Tags unique to parlor: gemma, litert-lm, kokoro, on-device-ai; Also covers Speech & Audio, Computer Vision.
When should I choose Agent-Reach over parlor?
Choose Agent-Reach over parlor when Agent-Reach is primarily Python; parlor is HTML; License: Agent-Reach is MIT, parlor 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 parlor?
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?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
Is parlor or Agent-Reach more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 1,894). Stars measure visibility, not whether either tool fits your constraints.
Are parlor and Agent-Reach open source?
Yes - both are open-source projects on GitHub (parlor: Apache-2.0, Agent-Reach: MIT).
Where can I find alternatives to parlor or Agent-Reach?
GraphCanon lists graph-backed alternatives at parlor alternatives and Agent-Reach alternatives (parlor 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, parlor or Agent-Reach?
parlor: 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 parlor and Agent-Reach?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: parlor trust report; Agent-Reach trust report.