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Connect CloudFront Cache Analyzer to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Get precise AWS CDN performance metrics and optimization logic.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through CloudFront Cache Analyzer.

  1. 01

    Analyze path patterns

    This capability evaluates how caching behavior changes across different URL paths. It helps you see if specific directories are missing the mark on hit ratios.

  2. 02

    Calculate cache metrics

    This capability computes hit ratios, origin load reduction, and data transfer metrics. It gives you the hard numbers on your current configuration efficiency.

  3. 03

    Calculate stale windows

    This capability defines the necessary SWR and SIE headers. It helps you set up better availability and lower latency during content revalidation.

  4. 04

    Get ttl optimization advice

    This capability provides specific TTL adjustments to improve your cache performance. Use it when your hit ratio isn't meeting your targets.

Real work

What teams actually run

01

Cost Reduction

You use the capability to find higher TTLs that reduce the amount of data being pulled from your origin.

02

Latency Improvement

You calculate stale-while-revalidate windows to serve content faster during revalidation.

03

Troubleshooting Cache Misses

You use path pattern analysis to find out why certain URLs aren't caching correctly.

04

Capacity Planning

You calculate origin load reduction to see if your current backend can handle expected traffic.

One connector, every AI

CloudFront Cache Analyzer works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put CloudFront Cache Analyzer to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

908ms average. Fast in production.

CloudFront Cache Analyzer is checked daily against the live service.

Daily averagePeak 1062ms
Oct 3Today
Fastest day
680ms
Slowest day
1062ms
14-day trend
Stable+2%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of CloudFront Cache Analyzer, so you can see the experience inside your AI.

It does not authenticate your account with CloudFront Cache Analyzer. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

CloudFront Cache Analyzer Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_pY3JBkhofLj9ZJ2P3hKHE0aLobhTrObLRMqTEYMH/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — CloudFront Cache Analyzer capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "cloudfront-cache-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_pY3JBkhofLj9ZJ2P3hKHE0aLobhTrObLRMqTEYMH/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up CloudFront Cache Analyzer in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work CloudFront Cache Analyzer owners hand off.

This is for engineers managing large scale content delivery on AWS. They use it to hand off complex CDN math to their AI agents.

  • 01

    Cloud Engineers

    They use the capability to verify that CloudFront configurations match their architectural goals.

  • 02

    DevOps Engineers

    They use it to reduce origin load and manage bandwidth costs.

  • 03

    Site Reliability Engineers

    They use it to optimize availability through better stale header management.

FAQ

Questions CloudFront Cache Analyzer owners ask.

  • 01

    How can I improve my CloudFront hit ratio?

    You can use the get_ttl_optimization_advice capability to find the right TTL adjustments for your specific workload.

  • 02

    Can this MCP help reduce my AWS bill?

    Yes, by calculating origin load reduction and optimizing bandwidth delivery through better caching strategies.

  • 03

    What is the difference between SWR and SIE?

    These are stale-while-revalidate and stale-if-error headers. The calculate_stale_windows capability helps you define the best values for both to improve availability.

  • 04

    Which AI clients can use this MCP?

    You can use this with any MCP-compatible client including Claude, Cursor, Windsurf, and VS Code.

  • 05

    Does this capability analyze specific URL paths?

    Yes, the analyze_path_patterns capability allows you to see how caching behavior varies across different parts of your site.

  • 06

    How can I reduce the load on my origin server?

    You can use calculate_cache_metrics to see how much load is being reduced. Increasing your TTL via get_ttl_optimization_advice can also help increase the cache hit ratio and further reduce origin requests.

  • 07

    What is the best way to handle stale content?

    Use calculate_stale_windows to determine the appropriate durations for stale-while-revalidate and stale-if-error headers to improve availability.

  • 08

    Can I analyze multiple paths at once?

    Yes, the analyze_path_patterns capability allows you to evaluate the caching health across multiple defined path patterns in a single report.

Explore

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