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Connect Retention Time Predictor 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. Model chromatographic behavior using QSRR-based molecular predictions.

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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 Retention Time Predictor.

  1. 01

    Compare column performance

    This capability predicts how switching between different column types changes retention behavior for a set of compounds.

  2. 02

    Predict retention time

    This capability calculates the expected retention time for a specific compound under your defined chromatographic conditions.

  3. 03

    Analyze gradient efficiency

    This capability evaluates how changes in mobile phase composition impact the elution profile.

  4. 04

    Calculate selectivity

    This capability determines how well two different compounds separate using a specific chromatographic setup.

Real work

What teams actually run

01

Method Pre-screening

Predict elution times for new compounds to decide if a specific column is worth testing.

02

Column Selection

Compare how different column types affect the retention of a specific compound set.

03

Gradient Optimization

Model how changing acetonitrile percentages affects the elution profile of an analyte.

04

Separation Assessment

Calculate selectivity between two analytes to ensure they will separate on a chosen setup.

One connector, every AI

Retention Time Predictor 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 Retention Time Predictor 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

910ms average. Fast in production.

Retention Time Predictor is checked daily against the live service.

Daily averagePeak 982ms
Oct 3Today
Fastest day
750ms
Slowest day
982ms
14-day trend
Slowing+8%

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 Retention Time Predictor, so you can see the experience inside your AI.

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

Retention Time Predictor Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_M0PT38z3MivutwkEfPwMglBOY6ljKAqgwCHO3ySw/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 — Retention Time Predictor capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "retention-time-predictor-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_M0PT38z3MivutwkEfPwMglBOY6ljKAqgwCHO3ySw/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 Retention Time Predictor in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Retention Time Predictor owners hand off.

Analytical chemists and lab researchers use this MCP to accelerate method development through digital simulation.

  • 01

    Analytical Chemists

    They hand off molecular structures and column specs to the AI to predict elution behavior.

  • 02

    Method Development Scientists

    They use the capability to compare column performance and gradient efficiency before physical testing.

  • 03

    Computational Chemists

    They leverage QSRR modeling to correlate structure with chromatographic properties.

FAQ

Questions Retention Time Predictor owners ask.

  • 01

    What is the basis for these retention predictions?

    The predictions are based on Quantitative Structure-Retention Relationships (QSRR) using molecular structure, column properties, and mobile phase composition.

  • 02

    Which AI clients can use this MCP?

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

  • 03

    Can I use this to optimize my gradient elution?

    Yes, the analyze_gradient_efficiency capability allows you to model how changes in mobile phase composition impact elution profiles.

  • 04

    Does this MCP require me to host anything?

    No, Vinkius hosts and manages the MCP for you. You just connect your client and start working.

  • 05

    Can I compare different columns?

    Yes, the compare_column_performance capability predicts how switching column types changes retention behavior for your compounds.

  • 06

    What inputs are required for retention time prediction?

    You must provide the SMILES string of the compound, the column properties (stationary phase, length, particle size), the mobile phase details, and the operating temperature.

  • 07

    Can I compare different columns for my compounds?

    Yes, use the compare_column_performance capability to predict how switching between different column types will change the retention behavior for a set of compounds.

  • 08

    How does temperature affect the results?

    The model applies temperature as a scaling factor to the base retention time, accounting for the increased kinetic energy and decreased interaction strength at higher temperatures.

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