Home/Compare/Agent-Reach vs jadx-ai-mcp

Comparison

Agent-Reach vs jadx-ai-mcp

Verdict

Pick Agent-Reach when agent-Reach is primarily Python; jadx-ai-mcp is Java; pick jadx-ai-mcp when jadx-ai-mcp is primarily Java; Agent-Reach is Python.

Markdown twin · Agent-Reach alternatives · jadx-ai-mcp alternatives

GraphCanon updated today

Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

55kpushed Jul 10, 2026
vs
jadx-ai-mcp logo

jadx-ai-mcp

zinja-coder/jadx-ai-mcp

2.5kpushed May 28, 2026

Trust & integrity

SignalAgent-Reachjadx-ai-mcp
Maintenance
Very active (0d since push)
As of today · github_public_v1
Steady (43d 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 MCP manifest
As of today · mcp_manifest

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.
jadx-ai-mcp
Plugin for JADX to integrate MCP server

Stars

Agent-Reach
55k
jadx-ai-mcp
2.5k

Forks

Agent-Reach
4.5k
jadx-ai-mcp
232

Open issues

Agent-Reach
144
jadx-ai-mcp
8

Language

Agent-Reach
Python
jadx-ai-mcp
Java

Adopt for

Agent-Reach
-
jadx-ai-mcp
-

Persona

Agent-Reach
-
jadx-ai-mcp
-

Runtime

Agent-Reach
-
jadx-ai-mcp
-

License

Agent-Reach
MIT
jadx-ai-mcp
Apache-2.0

Last pushed

Agent-Reach
Jul 10, 2026
jadx-ai-mcp
May 28, 2026

Categories

Agent-Reach
LLM Frameworks, AI Agents, Developer Tools
jadx-ai-mcp
LLM Frameworks, Developer Tools

Trust and health

Maintenance

Agent-Reach
Very active (96%)
jadx-ai-mcp
Steady (60%)

Days since push

Agent-Reach
0d
jadx-ai-mcp
43d

Open issues (now)

Agent-Reach
144
jadx-ai-mcp
8

Full report

Agent-Reach
Trust report
jadx-ai-mcp
Trust report

Choose Agent-Reach if…

  • Agent-Reach is primarily Python; jadx-ai-mcp is Java.
  • License: Agent-Reach is MIT, jadx-ai-mcp is Apache-2.0.
  • Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
  • Also covers 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 jadx-ai-mcp if…

  • jadx-ai-mcp is primarily Java; Agent-Reach is Python.
  • License: jadx-ai-mcp is Apache-2.0, Agent-Reach is MIT.
  • Tags unique to jadx-ai-mcp: mcp-server, llm, ai, model-context-protocol.

When NOT to use jadx-ai-mcp

  • 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: Agent-Reach 55k · jadx-ai-mcp 2.5k (synced Jul 11, 2026).

Common questions

What is the difference between Agent-Reach and jadx-ai-mcp?
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.. jadx-ai-mcp: Plugin for JADX to integrate MCP server. See the comparison table for live GitHub stats and shared categories.
When should I choose Agent-Reach over jadx-ai-mcp?
Choose Agent-Reach over jadx-ai-mcp when Agent-Reach is primarily Python; jadx-ai-mcp is Java; License: Agent-Reach is MIT, jadx-ai-mcp is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents.
When should I choose jadx-ai-mcp over Agent-Reach?
Choose jadx-ai-mcp over Agent-Reach when jadx-ai-mcp is primarily Java; Agent-Reach is Python; License: jadx-ai-mcp is Apache-2.0, Agent-Reach is MIT; Tags unique to jadx-ai-mcp: mcp-server, llm, ai, model-context-protocol.
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 jadx-ai-mcp?
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 Agent-Reach or jadx-ai-mcp more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 2,463). Stars measure visibility, not whether either tool fits your constraints.
Are Agent-Reach and jadx-ai-mcp open source?
Yes - both are open-source projects on GitHub (Agent-Reach: MIT, jadx-ai-mcp: Apache-2.0).
Where can I find alternatives to Agent-Reach or jadx-ai-mcp?
GraphCanon lists graph-backed alternatives at Agent-Reach alternatives and jadx-ai-mcp alternatives (Agent-Reach markdown twin, jadx-ai-mcp 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 jadx-ai-mcp?
Agent-Reach: Very active. jadx-ai-mcp: 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 jadx-ai-mcp?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agent-Reach trust report; jadx-ai-mcp trust report.