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Debugging AWS with MCP and AI Assistants

When something breaks in AWS, the answer is usually spread across the console, your repositories, your monitoring tools and your CI history. AI assistants are great at reasoning about problems, but they don't know your infrastructure. MCP (Model Context Protocol) lets an assistant like Claude or ChatGPT fetch real facts during the conversation. This article explains how to use it for AWS debugging, safely.

What MCP changes for debugging

Without MCP, you copy and paste. You export configurations, paste log lines and describe your architecture from memory, and the assistant reasons from whatever you gave it. With an MCP connector, the assistant can look facts up itself:

  • What a resource is connected to and what it's exposed to.
  • Which recent deployment overlaps with an error spike.
  • Where in the code a timeout or limit is configured.

Principles for using MCP with production AWS

  1. Read-only access. Debugging tools should never be able to change infrastructure. Use read-only credentials or an assumed role.
  2. Show where each fact came from. Every fact the assistant uses should identify its source, so you can check it before acting.
  3. Missing data isn't zero. "No resources found" only means something if that area was actually scanned. An unscanned, unsupported or throttled scan must not look like an empty result.
  4. Keep credentials away from the AI. The assistant should retrieve facts, not hold your AWS keys.

A debugging session, step by step

With an AWS-aware MCP connector enabled in your assistant:

  1. Start specific: "Is checkout erroring? Show me the last 15 minutes."
  2. Find the change: "Which recent deployment overlaps with the error increase?"
  3. Check the blast radius: "If this database goes down, what breaks?"
  4. Find the code: "Where in the code is the payment timeout configured?"
  5. Check the evidence: "Where did each result come from?"

Doing this with Vörr

Vörr is a read-only engineering context engine that connects to Claude and ChatGPT through a single MCP connector. It links your AWS accounts with your repositories, observability tools and CI, so one question can draw on all of them.

  • Connect AWS with an access key or an assumed role, using read-only credentials. Credentials are encrypted and masked once saved.
  • Run a scan to discover and map your supported resources. Scans only read and never modify anything.
  • Check scan coverage. Vörr separates a scanned-and-empty result from a resource type it doesn't index and from a scan that was incomplete because of access, failure or throttling. Only the first is a trustworthy zero.
  • Add Vörr to Claude or ChatGPT. Copy the MCP URL from Vörr and add it as a custom connector. Authorizing the connector doesn't expose your stored AWS credentials to the assistant.
  • Read the provenance. Answers identify the source of each fact and how services were matched: explicit, inferred or unmapped.

Vörr also supports Azure and Google Cloud.

FAQ

Can Vörr change my AWS resources?

No. Vörr is read-only by design and doesn't change your infrastructure, code or CI.

Does the AI assistant get my AWS keys?

No. The connector authorization is tied to your user and organisation, and it doesn't expose Vörr's stored credentials.