--- title: "Agent-Reach vs jadx-ai-mcp" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/panniantong-agent-reach-vs-zinja-coder-jadx-ai-mcp" tools: ["panniantong-agent-reach", "zinja-coder-jadx-ai-mcp"] --- # Agent-Reach vs jadx-ai-mcp *GraphCanon updated Jul 11, 2026* ## 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. [Agent-Reach](https://github.com/Panniantong/Agent-Reach) reports 55k GitHub stars, 4.5k forks, and 144 open issues, last pushed Jul 10, 2026. [jadx-ai-mcp](https://github.com/zinja-coder/jadx-ai-mcp) has 2.5k stars, 232 forks, and 8 open issues, last pushed May 28, 2026. Figures are from public GitHub metadata via [Agent-Reach's repository](https://github.com/Panniantong/Agent-Reach) and [jadx-ai-mcp's repository](https://github.com/zinja-coder/jadx-ai-mcp). | | [Agent-Reach](/tools/panniantong-agent-reach.md) | [jadx-ai-mcp](/tools/zinja-coder-jadx-ai-mcp.md) | | --- | --- | --- | | Tagline | Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees. | Plugin for JADX to integrate MCP server | | Stars | 54,715 | 2,463 | | Forks | 4,509 | 232 | | Open issues | 144 | 8 | | Language | Python | Java | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | LLM Frameworks, AI Agents, Developer Tools | LLM Frameworks, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Agent-Reach](/tools/panniantong-agent-reach.md) | [jadx-ai-mcp](/tools/zinja-coder-jadx-ai-mcp.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 43d | | Open issues (now) | 144 | 8 | | Full report | [trust report](/tools/panniantong-agent-reach/trust.md) | [trust report](/tools/zinja-coder-jadx-ai-mcp/trust.md) | ## Choose when ### 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. ### 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 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 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. ## 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](/tools/panniantong-agent-reach/alternatives) and [jadx-ai-mcp alternatives](/tools/zinja-coder-jadx-ai-mcp/alternatives) ([Agent-Reach markdown twin](/tools/panniantong-agent-reach/alternatives.md), [jadx-ai-mcp markdown twin](/tools/zinja-coder-jadx-ai-mcp/alternatives.md)), 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](/compare/panniantong-agent-reach-vs-zinja-coder-jadx-ai-mcp.md) 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](/tools/panniantong-agent-reach/trust); [jadx-ai-mcp trust report](/tools/zinja-coder-jadx-ai-mcp/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=panniantong-agent-reach`](/api/graphcanon/graph?tool=panniantong-agent-reach) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_