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MCP server · Documentation

Rocketride Server

· github.com/rocketride-org/rocketride-server

High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.

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Scored 6 months ago · breakdown

About Rocketride Server

Rocketride Server is an MCP server in the Documentation category: high-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.

Install

From source
git clone https://github.com/rocketride-org/rocketride-server

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

Design, test, and ship complex AI workflows from a visual canvas, right where you write code.

Drop pipelines into any Python or TypeScript app with a few lines of code, no infrastructure glue required.

Features

Feature Description
Visual Pipeline Builder Drag, connect, and configure nodes in VS Code — no boilerplate. Real-time observability tracks token usage, LLM calls, latency, and execution. Pipelines are portable JSON — version-controllable, shareable, and runnable anywhere.
High-Performance C++ Runtime Native multithreading purpose-built for the throughput demands of AI and data workloads. No bottlenecks, no compromises for production scale.
50+ Pipeline Nodes 13 LLM providers, 8 vector databases, OCR, NER, PII anonymization, chunking strategies, embedding models, and more. All nodes are Python-extensible — build and publish your own.
Multi-Agent Workflows Built-in CrewAI and LangChain support. Chain agents, share memory across pipeline runs, and manage multi-step reasoning at scale.
Coding Agent Ready RocketRide auto-detects your coding agent — Claude, Cursor, and more. Build, modify, and deploy pipelines through natural language.
TypeScript, Python & MCP SDKs Integrate pipelines into native apps, expose them as callable tools for AI assistants, or build programmatic workflows into your existing codebase.
Zero Dependency Headaches Python environments, C++ toolchains, Java/Tika, and all node dependencies managed automatically. Clone, build, run — no manual setup.
One-Click Deploy Run on Docker, on-prem, or RocketRide Cloud (coming soon). Production-ready architecture from day one — not retrofitted from a demo.

Quick Start

  1. Install the extension for your IDE. Search for RocketRide in the extension marketplace:

    Not seeing your IDE? Open an issue · Download directly

  2. Click the RocketRide extension in your IDE

  3. Deploy a server - you'll be prompted on how you want to run the server. Choose the option that fits your setup:

    • Local (Recommended) - This pulls the server directly into your IDE without any additional setup.
    • On-Premises - Run the server on your own hardware for full control and data residency. Pull the image and deploy to Docker or clone this repo and build from source.

Building Your First Pipe

  1. All pipelines are recognized with the *.pipe format. Each pipeline and its configuration are JSON objects - but the extension in your IDE will render within our visual builder canvas.

  2. All pipelines begin with a source node: webhook, chat, or dropper. For specific usage, examples, and inspiration on how to build pipelines, check out our guides and documentation.

  3. Connect input lanes and output lanes by type to properly wire your pipeline. Some nodes like agents or LLMs can be invoked as tools for use by a parent node as shown below:

  1. You can run a pipeline from the canvas by pressing the ▶ button on the source node or from the Connection Manager directly.

  2. Deploy your pipelines on your own infrastructure.

    • Docker - Download the RocketRide server image and create a container. Requires Docker to be installed.

      docker pull ghcr.io/rocketride-org/rocketride-engine:latest
docker create --name rocketride-engine -p 5565:5565 ghcr.io/rocketride-org/rocketride-engine:latest

    • Local Deployment - Download your preferred runtime as a standalone process from the Deploy page in the Connection Manager.

  3. Run your pipelines as standalone processes or integrate them into your existing Python and TypeScript/JS applications utilizing our SDK.

Observability

Selecting running pipelines allows for in-depth analytics. Trace call trees, token usage, memory consumption, and more to optimize your pipelines before scaling and deploying. Find the models, agents, and tools best fit for your task.

Contributors

RocketRide is built by a growing community of contributors. Whether you've fixed a bug, added a node, improved docs, or helped someone on Discord, thank you. New contributions are always welcome - check out our contributing guide to get started.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Rocketride Server

How do I install Rocketride Server?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Rocketride Server safe to use with an AI agent?

Its trust score is 64 out of 100 (good). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Rocketride Server still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.