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Side-by-side MCP evidence comparison
Evidence fieldJADX-AI-MCP (Part of Zin MCP Suite)MCP100 SelectedSequential Thinking MCPMCP100 Selected
Task fit
Best for
  • Navigating JADX decompilation, searching APK code, and accelerating reverse-engineering or security-analysis hypotheses
  • Complex planning and debugging that benefits from revisions and branches
  • MCP demonstrations with a small single-purpose tool surface
  • Local workflows that do not require an external SaaS integration
Not ideal for
  • Definitive vulnerability certification, dynamic analysis, or reviewing applications without authorization
  • Simple questions where repeated reasoning calls add latency and tokens
  • Applications that should not surface or persist detailed reasoning traces
  • Workflows needing domain data or external actions
Avoid when
  • APK contents, decompiled code, or findings cannot be shared with the connected AI client
  • The host records tool arguments and sensitive reasoning must remain undisclosed
  • Strict token or latency budgets cannot tolerate repeated tool calls
  • Package execution through npx is prohibited by supply-chain policy
Provenance
Provenance details

Community implementation

github:zinja-coder · Publisher source ↗

Ecosystem official

Model Context Protocol · Publisher source ↗

Maintenance
Maintenance details

Repo: Aug 6, 2026

Package: Not documented

Repo: Aug 10, 2026

Package: Jul 4, 2026

Popularity evidence
GitHub stars

2,664

GitHub stars · checked 2026-08-14T18:46:26.000Z

Not documented
30-day package downloadsNo reliable download data

144,449

30-day package downloads · checked 2026-07-29T17:30:00.000Z

Shared repository starsNot documented

89,561

Shared repository stars (not MCP-specific) · checked 2026-08-14T18:46:26.000Z

External adoption evidence
  • github: repository stars: 2,664Exact attributable signal.github: repository stars · Admission snapshot · checked 2026-08-14T18:46:26.000ZEvidence source ↗
  • npm: package downloads: 144,449Exact attributable signal.npm: package downloads · Admission snapshot · checked 2026-07-29T17:30:00.000ZEvidence source ↗
  • github: repository stars: 89,561Non-comparable contextual signal.github: repository stars · Admission snapshot · checked 2026-08-14T18:46:26.000ZEvidence source ↗
Client coverage
Client coverage details
Claude Code✓ Local stdio
Claude Desktop✓ Local stdio
Codex✓ Local stdio
VS Code✓ Local stdio
Cursor✓ Local stdio
OpenCode✓ Local stdio
Claude Code✓ Local stdio
Claude Desktop✓ Local stdio
Codex✓ Local stdio
VS Code✓ Local stdio
Cursor✓ Local stdio
OpenCode✓ Local stdio
Client coverage noteLocal stdio runs on your computer. Streamable HTTP connects to a remotely hosted MCP server.
Access and data
AuthenticationThe documented default is stdio with the HTTP endpoints on 127.0.0.1. The publisher explicitly warns that binding the MCP server to 0.0.0.0 or another non-localhost address exposes plain HTTP with no authentication or TLS, allowing anyone on that network to invoke all tools.None.
CostThe publisher distributes the project under the Apache License 2.0 and lists no MCP server usage fee. JADX, local compute, the selected MCP client, and model-provider costs can still apply.The ecosystem-official reference package is MIT licensed and has no service fee. Model tokens, local compute, and MCP-host costs remain.
PermissionsThe published tools can read decompiled code for classes and methods, smali, AndroidManifest.xml, string and resource files, cross-references, and debugger frames, threads, and variables from the project open in JADX. They can also rename classes, methods, fields, packages, and variables within the JADX analysis workspace.No external service scopes are required. The local process receives thought text and reasoning metadata from the MCP host and returns structured reasoning state.
Data handlingThe publisher's architecture sends tool requests from the LLM client through the Python MCP server over HTTP to the JADX-GUI plugin, then returns source, resource, manifest, and debugger data to the connected client. The reviewed README does not document telemetry, retention, or model-training use, so those behaviors remain unknown.Reasoning text is processed by the local stdio server. The connected MCP host, model provider, and their logs may still transmit or retain tool arguments according to their own policies. Thought logging can be disabled with DISABLE_THOUGHT_LOGGING=true.
Limitations
Tradeoffs
  • JADX integration speeds static exploration, but decompilation is imperfect and AI-generated security conclusions can contain false positives or miss runtime behavior.
  • Its single-tool scope keeps permissions small but provides no external facts or actions.
  • Structured thought history supports revision while increasing context use and potential telemetry exposure.
  • The package is easy to run with npx, while stricter environments may require a pinned version or container digest.
Risk contextThis server exposes sensitive reverse-engineering material and mutation tools for the APK project open in JADX. Keep both connections on 127.0.0.1 and prefer stdio; if remote access is unavoidable, use a trusted isolated network plus firewall or SSH tunnel. Treat decompiled source, resources, manifests, and debugger values as potentially confidential, and review rename operations before saving or exporting analysis artifacts.System permissions are low, but prompts and reasoning can contain secrets and repeated calls can increase token cost. Keep sensitive material out of thought text, disable thought logging where appropriate, and use an approved package version.
Evidence date
Editorial review2026-08-112026-07-24
Candidate evidence2026-08-14T18:46:26.000Z2026-08-14T18:46:26.000Z

Popularity, maintenance, fit, permissions, and client support are independent evidence fields.

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