deephaven/deephaven-mcp

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Repository Install

Deephaven Model Context Protocol

Обзор

Command names, flags, and output shapes can change without notice, so an upgrade may break scripts written against them — pin a version if you need stability. AI agents need no such care: dhcli describes itself at runtime through dhcli agents tree and --agents, so an agent that reads that manifest adapts to the changes on its own. Deephaven MCP brings the power of live dataframes directly to your favorite AI tools — Claude Desktop, Cursor, VS Code (GitHub Copilot), Windsurf, and more. Working with real-time data usually means giving up the simple, interactive workflow you get with static tables. Deephaven's live dataframes remove that trade-off: write queries as if your data were static and they keep updating automatically as new data streams in, all through natural language.

README

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deephaven-mcp

The dhcli command-line tool is under rapid development. Command names, flags, and output shapes can change without notice, so an upgrade may break scripts written against them — pin a version if you need stability. AI agents need no such care: dhcli describes itself at runtime through dhcli agents tree and --agents, so an agent that reads that manifest adapts to the changes on its own.

Overview
Key Use Cases
Quick Start
Quick Upgrade
Deephaven MCP Components
Available MCP Tools
Architecture Diagrams
Prerequisites
Installation & Initial Setup
Configuration
AI Tool Setup
Troubleshooting
Contributing
Community & Support
License

Overview

Supercharge your AI workflows with real-time data. Deephaven MCP brings the power of live dataframes directly to your favorite AI tools — Claude Desktop, Cursor, VS Code (GitHub Copilot), Windsurf, and more.

Why Deephaven MCP?

Working with real-time data usually means giving up the simple, interactive workflow you get with static tables. Deephaven’s live dataframes remove that trade-off: write queries as if your data were static and they keep updating automatically as new data streams in, all through natural language.

What makes this different:

Live Data, Live Results: Query streaming Kafka, real-time feeds, and batch data as easily as static CSV files
AI-Native Integration: Your AI assistant understands your data pipeline and can help optimize, debug, and extend it
Enterprise Ready: Battle-tested on Wall Street for over a decade, now available for your team
Zero Learning Curve: Write queries as if working with static tables — real-time updates happen automatically

Deephaven MCP implements the Model Context Protocol (MCP)

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Установка

This server does not publish a one-line install command.

Open the repository installation guide Новичок в MCP? Начните с руководства на mcpskill.org →

Конфигурация

{
  "mcpServers": {
    "deephaven-systems": {
      "command": "dh-mcp-systems-server",
      "args": ["--transport", "stdio"]
    },
    "deephaven-docs": {
      "command": "mcp-proxy",
      "args": [
        "--transport=streamablehttp",
        "https://deephaven-mcp-docs-prod.dhc-demo.deephaven.io/mcp"
      ]
    }
  }
}