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Connect Lambda Resource Optimizer 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 resource estimates for your AWS Lambda functions.

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 · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through AWS Lambda Optimizer.

  1. 01

    Estimate concurrency requirements

    This capability calculates the concurrency needed to handle your expected load. It helps you plan for peak traffic periods.

  2. 02

    Calculate resource optimization

    This capability finds the ideal memory and CPU allocation for your function. It uses your code size to determine the most efficient tier.

  3. 03

    Validate lambda constraints

    This capability checks your configurations against AWS service limits. It prevents you from deploying settings that exceed regional quotas.

Real work

What teams actually run

01

Cost Optimization

You can find the lowest memory tier that still meets your performance needs to lower your AWS bill.

02

Scaling Preparation

Use it to determine if your current regional concurrency limits can handle an upcoming traffic surge.

03

Deployment Safety

Check your function settings before you deploy to ensure you aren't requesting more memory than AWS allows.

04

Performance Tuning

Match your CPU needs to your code size to ensure your functions run fast enough for your users.

One connector, every AI

AWS Lambda Optimizer 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 AWS Lambda Optimizer 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

888ms average. Fast in production.

AWS Lambda Optimizer is checked daily against the live service.

Daily averagePeak 988ms
Oct 3Today
Fastest day
673ms
Slowest day
988ms
14-day trend
Improving-9%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 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 AWS Lambda Optimizer, so you can see the experience inside your AI.

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

AWS Lambda Optimizer Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_5lhJ74NEi6LOP5MdGOqCLzQ3NGkoKMrSMW5s2cwj/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 — AWS Lambda Optimizer capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "lambda-resource-optimizer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_5lhJ74NEi6LOP5MdGOqCLzQ3NGkoKMrSMW5s2cwj/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 AWS Lambda Optimizer in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AWS Lambda Optimizer owners hand off.

This MCP is built for engineers managing serverless architectures who need to balance performance and cost.

  • 01

    DevOps Engineers

    They use the MCP to ensure functions stay within regional quotas and service limits.

  • 02

    Backend Developers

    They use it to find the most efficient memory settings for their specific code packages.

  • 03

    Cloud Architects

    They use it to plan for scale and predict concurrency requirements for new services.

FAQ

Questions AWS Lambda Optimizer owners ask.

  • 01

    How does this MCP calculate memory requirements?

    It uses your zipped code size to determine the minimum required memory and then rounds to the nearest valid 64 MB increment.

  • 02

    Can I use this with Claude or Cursor?

    Yes, you can connect this MCP to any MCP-compatible client including Claude, Cursor, and Windsurf.

  • 03

    What is the maximum memory limit for AWS Lambda?

    The maximum allowed memory allocation for a Lambda function is 10240 MB.

  • 04

    Does this MCP help with AWS service limits?

    Yes, the validate_lambda_constraints capability checks your settings to ensure they don't violate regional quotas.

  • 05

    How does it handle CPU allocation?

    The MCP calculates the vCPU you receive based on the memory tier you select.

  • 06

    How is the minimum memory calculated?

    The minimum required memory is calculated as three times the zipped code size plus a fixed 300 MB overhead.

  • 07

    Can I check if my Lambda configuration is valid?

    Yes, you can use the validate_lambda_constraints capability to check if your memory and timeout settings violate AWS service limits.

  • 08

    How does CPU scaling work in this capability?

    The capability calculates CPU allocation proportionally, providing one full vCPU for every 1769 MB of memory allocated.

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