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RocketRide

v1.0.0โ€ขData Science & MLโ€ขstable

๐Ÿ“‡ ๐Ÿ  - MCP server that exposes RocketRide AI pipelines as t

aicppdata-pipelinedata-processingmachine-learning
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What is RocketRide?

RocketRide is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to ๐Ÿ“‡ ๐Ÿ  - mcp server that exposes rocketride ai pipelines as t

๐Ÿ“‡ ๐Ÿ  - MCP server that exposes RocketRide AI pipelines as t

This server falls under the Data Science & ML category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • MCP protocol support

Use Cases

Expose AI pipelines as MCP tools
Data processing and machine learning workflows
rocketride-org

Maintainer

LicenseMIT License
Languagec++
Versionv1.0.0
UpdatedMay 22, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux
View SourceBrowse All Servers

Installation

Manual Installation

npx rocketride

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use RocketRide

RocketRide is a data pipeline platform that exposes its AI pipeline creation, editing, and execution capabilities as MCP tools so that coding agents like Claude can build and modify pipelines through natural language. The platform supports 85+ pipeline node types spanning 13 LLM providers, 8 vector databases, OCR, NER, and multi-agent orchestration frameworks like CrewAI and LangChain. With the rocketride-mcp Python package, any MCP-compatible client can design, deploy, and monitor RocketRide pipelines without using the visual UI.

Prerequisites

  • Python 3.9+ for the rocketride-mcp package
  • A RocketRide account or local RocketRide server instance
  • pip or uv for installing the Python MCP package
  • An MCP-compatible client such as Claude Desktop or VS Code with the RocketRide extension
  • API keys for the LLM providers you intend to use in your pipelines
1

Install the rocketride-mcp package

Install the RocketRide MCP server package from PyPI using pip.

pip install rocketride-mcp
2

Configure Claude Desktop to use the MCP server

Add the rocketride-mcp server to your claude_desktop_config.json. The server runs as a Python module.

{
  "mcpServers": {
    "rocketride": {
      "command": "python",
      "args": ["-m", "rocketride_mcp"]
    }
  }
}
3

Restart Claude Desktop

Fully quit and reopen Claude Desktop to load the new MCP server configuration. Check that the RocketRide tools appear in the tool list.

4

Connect to your RocketRide instance

If your RocketRide server is running on a non-default host or port, configure the connection settings. The MCP server typically reads these from environment variables or a config file in your working directory.

# Example: set connection env vars before starting the MCP server
export ROCKETRIDE_SERVER_URL=http://localhost:8080
export ROCKETRIDE_API_KEY=your_api_key
5

Design your first pipeline via Claude

Ask Claude to create a pipeline using natural language. The MCP tools translate your intent into a .pipe JSON file that RocketRide executes.

RocketRide Examples

Client configuration

Claude Desktop configuration for the RocketRide MCP server running as a Python module.

{
  "mcpServers": {
    "rocketride": {
      "command": "python",
      "args": ["-m", "rocketride_mcp"],
      "env": {
        "ROCKETRIDE_SERVER_URL": "http://localhost:8080",
        "ROCKETRIDE_API_KEY": "your_rocketride_api_key"
      }
    }
  }
}

Prompts to try

Use these prompts to design and manage RocketRide pipelines through your MCP client.

- "Build me an AI search pipeline that takes a query, searches a Pinecone vector database, and returns the top 5 results"
- "Create an OCR pipeline that processes PDF uploads and extracts structured text"
- "Show me all existing pipelines and their current execution status"
- "Modify the customer-support pipeline to add a sentiment analysis node before the response generation step"
- "Deploy the invoice-parser pipeline to Docker and give me the endpoint URL"

Troubleshooting RocketRide

pip install rocketride-mcp fails with a package not found error

Verify the package name at https://pypi.org/project/rocketride-mcp/. If unavailable, clone https://github.com/rocketride-org/rocketride-server and follow the local installation instructions in the repository.

The MCP server starts but Claude cannot connect to the RocketRide backend

Confirm that your RocketRide server is running and that ROCKETRIDE_SERVER_URL points to the correct host and port. Check firewall rules if running on a remote server.

Pipeline creation fails with a node type not found error

Verify that your RocketRide version supports the requested node type. Run a tool call to list available nodes first, then reference only those node types in your pipeline design prompts.

Frequently Asked Questions about RocketRide

What is RocketRide?

RocketRide is a Model Context Protocol (MCP) server that ๐Ÿ“‡ ๐Ÿ  - mcp server that exposes rocketride ai pipelines as t It connects AI assistants to external tools and data sources through a standardized interface.

How do I install RocketRide?

Follow the installation instructions on the RocketRide GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with RocketRide?

RocketRide works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is RocketRide free to use?

Yes, RocketRide is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.

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Quick Config Preview

{ "mcpServers": { "rocketride": { "command": "npx", "args": ["-y", "rocketride"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide โ†’

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