Retention Time PredictorをChatGPTとClaudeに接続

最速日

750ms

最遅日

982ms

14日間の傾向

遅延傾向+8%

Retention Time Predictor Connector

準備完了です。MCPクライアントを選択し、セットアップ手順に従ってください。

コネクタリンクhttps://edge.vinkius.com/vk_preview_M0PT38z3MivutwkEfPwMglBOY6ljKAqgwCHO3ySw/mcpコピー

Claude Desktop

以下の手順で数秒で接続できます。

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.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "retention-time-predictor-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_M0PT38z3MivutwkEfPwMglBOY6ljKAqgwCHO3ySw/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

各クライアントの手順ガイドはこちらです。 接続方法

Claude向けのガイド付きセットアップ？ Retention Time PredictorをClaudeや他のAIに設定する

このConnectorが対応するすべてのAIクライアントを見る ↑

• 01

  分析化学者

  クロマトグラフィーの分離条件の最適化や、新しい分離手法の検討に利用できます。

• 02

  製薬研究員

  化合物の構造に基づいた保持挙動の予測により、実験回数の削減と効率化を図れます。

• 03

  ラボ自動化エンジニア

  AIエージェントと連携させ、計算化学に基づいた実験プロトコルの自動生成に活用できます。

• 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.

• 

  Cohort Retention Analytics AIコネクタ

  Analyze cohort retention curves, average user lifetime, and benchmark performance against industry standards.

  表示
• 

  Chromatography Method Development AIコネクタ

  Automate chromatography method selection, column recommendation, and resolution prediction.

  表示
• 

  Transition Metal Chemistry Predictor AIコネクタ

  Predict electronic, magnetic, and optical properties of transition metal complexes.

  表示
• 

  QuestDB (Time-Series) AIコネクタ

  High-performance time-series database for fast SQL queries, data ingestion, and real-time analytics directly f

  表示

おすすめ

• 

  Time-Series Seasonality Engine AIコネクタ

  Compute exact Autocorrelation (ACF) to find seasonality lags in time-series data without hallucination.

  表示
• 

  Timeero AIコネクタ

  Track employee time and mileage with GPS-verified clock-ins that generate accurate timesheets for field servic

  表示
• 

  GitScrum Time Tracking AIコネクタ

  Track time and budgets via GitScrum — start timers, log hours, analyze productivity, monitor burn-down, and re

  表示
• 

  Time-Zone Insulin Adjuster AIコネクタ

  Deterministic basal insulin and meal timing adjustment calculator for travel.

  表示