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Connect Aws Timestream Sizing Calculator to your AI

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. Accurately size your time-series database infrastructure.

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 Timestream.

  1. 01

    Calculate architectural hierarchy

    Estimates the distribution of data across the AWS Timestream organizational structure

  2. 02

    Calculate ingestion and storage

    Calculates primary data flow metrics including throughput and storage volume across both tiers

  3. 03

    Calculate operational limits

    Determines optimized write batching strategies and query execution capacity

Real work

What teams actually run

01

Launching a New Monitoring System

You are starting a new product that tracks sensor data every second. You use this MCP to calculate the required ingestion rate and total storage volume for the first year.

02

Scaling an Existing Dashboard

Your current system is hitting performance bottlenecks. You run this MCP to determine if you need to increase query concurrency or adjust your data retention policy.

03

Designing a Financial Tracker

You need to store millions of stock price measures. You use the MCP to plan the architectural hierarchy, ensuring the data is distributed correctly across databases.

04

Analyzing IoT Sensor Data

You are ingesting data from thousands of devices. You use this MCP to calculate the necessary write batching strategies to handle the massive, continuous data stream.

One connector, every AI

AWS Timestream 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 Timestream 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

915ms average. Fast in production.

AWS Timestream is checked daily against the live service.

Daily averagePeak 1112ms
Oct 3Today
Fastest day
639ms
Slowest day
1112ms
14-day trend
Improving-12%

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 Timestream, so you can see the experience inside your AI.

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

AWS Timestream Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_7dS8jv4W6XgCvSE4oUZxxpdC3EQjVW0f2cOZKrBB/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 Timestream capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "aws-timestream-sizing-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_7dS8jv4W6XgCvSE4oUZxxpdC3EQjVW0f2cOZKrBB/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 Timestream in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AWS Timestream owners hand off.

This MCP is essential for data architects and infrastructure engineers. If you're building a new application that tracks metrics over time, you need to know the limits before you deploy. It gives you the hard numbers required to size the database correctly, saving you time and money on cloud resources.

  • 01

    Data Architect

    Designs the overall data flow and determines the optimal organizational structure for the time-series data.

  • 02

    Infrastructure Engineer

    Calculates the required throughput and operational limits to ensure the database can handle peak load without failure.

  • 03

    Data Scientist

    Needs to know the storage and retention limits to ensure historical data is available for long-term analysis.

FAQ

Questions AWS Timestream owners ask.

  • 01

    Is this MCP only for AWS Timestream?

    Yes. This connector is specifically designed for the AWS Timestream database. It uses the unique architectural and operational rules of that service to provide accurate sizing estimates.

  • 02

    What kind of data can I use this for?

    It is built for time-series data. This includes metrics, sensor readings, stock prices, and any data that is tracked over a continuous period of time.

  • 03

    Do I need to provide actual data samples?

    No. You provide the metrics, like '500 measures per second' or '1,000,000 total measures,' and the MCP uses those numbers to run the deterministic calculations.

  • 04

    Can this help me reduce cloud costs?

    Yes. By providing precise sizing, you avoid the common mistake of over-provisioning resources, which directly translates to lower cloud spending.

  • 05

    How do I estimate my storage costs?

    You can use the calculate_ingestion_and_storage capability to estimate the volume of data in both the Memory and Magnetic storage tiers, which helps in predicting AWS Timestream costs.

  • 06

    Can I plan my database hierarchy?

    Yes, the calculate_architectural_hierarchy capability estimates the distribution of data across dimensions, tables, databases, and accounts based on your total measure count.

  • 07

    How can I optimize my write operations?

    Use the calculate_operational_limits capability to find the optimal batch size in records and MB, as well as recommended query concurrency levels.

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