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DimensionAnything Analyzer MCP ServerCross-scenario traffic capture and protocol analysis for AI agents.NPM Sentinel MCP ServerAI-powered NPM package analysis MCP server
FMRS27 / 100 · D79 / 100 · B
Reliability3 / 2012 / 20
Security and permissions5 / 2016 / 20
Maintenance4 / 2018 / 20
Documentation9 / 2018 / 20
Setup experience6 / 2015 / 20
Best for
  • Developers who need one workflow for browser, application, terminal, and mobile traffic
  • Researchers conducting authorized protocol reverse engineering, API debugging, or security audits
  • Users who want an AI agent to help interpret HTTP traffic
  • Developers auditing NPM dependencies within AI workflows
  • Teams performing supply chain security assessments
  • Users of Claude Desktop, Cursor, or VS Code
Not for
  • Unauthorized intrusion, data acquisition, or system control
  • Active proxy workflows that require modifying requests or responses
  • Use cases requiring decrypted WebSocket contents
  • Users seeking a built-in AI model without configuring an external model API
  • Projects outside the NPM ecosystem (e.g., pure Python/Go)
  • Environments without network access to deps.dev, OSV.dev, and the npm registry
  • Scenarios requiring maintenance by an official upstream vendor
Required permissions
  • AI analysis requires an API key for OpenAI, Anthropic, or a compatible API
  • HTTPS MITM capture requires installing and managing a local CA certificate
  • Changing system proxy settings may require operating-system permissions
  • The proxy can access request and response headers and bodies, plus Cookie, localStorage, and sessionStorage snapshots
  • Network access to the NPM registry and external services (deps.dev, OSV.dev, OpenSSF, npms.io, GitHub)
  • Read access to workspace lockfiles (pnpm-lock.yaml, package-lock., yarn.lock) for cache invalidation
Risks and side effects
  • Captured traffic may contain tokens, cookies, credentials, or other sensitive data
  • Installing a local CA certificate and enabling a system proxy increases the visibility of local traffic
  • Sending captured data to an external LLM service can create privacy and compliance risks
  • Bodies are limited to 1 MB and binary content is skipped; WebSocket traffic is tunneled rather than decrypted
  • Third-party READMEs and changelogs are untrusted external content; they are wrapped in tags with _meta flags but should still be handled cautiously
  • Depends on availability and accuracy of external services
  • Batch requests are capped at 25 packages to prevent registry enumeration; larger sets require batching
  • Third-party open source project, not officially maintained by NPM or Anthropic
Supported clientsClaude Desktop, CursorClaude Desktop, VS Code, Cursor
Tools019