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.
RocketRide MCP server exposes a high-performance AI pipeline engine to Model Context Protocol clients, enabling assistants to build and execute complex LLM workflows. The server wraps RocketRide's C++ runtime, which orchestrates pipelines across 15+ language model providers, 9 vector databases, and 100+ specialized nodes for OCR, NER, embeddings, and multi-agent orchestration. Developers can design visual pipelines in VS Code, then invoke them programmatically through the MCP interface or integrate them into Python and TypeScript applications. Pipelines are defined as portable JSON, version-controlled alongside code, and execute either locally, on-premises via Docker, or on managed RocketRide Cloud infrastructure.
Key Features
Use Cases
- 01Exposing reusable AI pipelines as callable tools within Claude Desktop or other MCP-compatible clients
- 02Building multimodal AI search systems combining vector databases, embeddings, and LLM re-ranking
- 03Orchestrating multi-step agent workflows with shared memory and tool invocation across pipeline stages
- 04Processing documents with OCR, chunking, embedding generation, and vector storage in a single pipeline
- 05Developing and debugging LLM applications with built-in tracing and token usage analytics
- 06Deploying production-ready AI workflows with the same pipeline JSON used during local development
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rocketride-server — FAQ
What is the RocketRide MCP server?+
The RocketRide MCP server is a Model Context Protocol interface to RocketRide's AI pipeline engine, allowing AI assistants and clients to build, execute, and manage complex LLM workflows involving multiple model providers, vector databases, and processing nodes. It exposes pipeline operations as MCP tools that can be invoked from compatible clients like Claude Desktop.
How do I install the RocketRide MCP server?+
Install the RocketRide VS Code extension from the marketplace, then deploy the server locally (embedded in the IDE), via Docker using the ghcr.io/rocketride-org/rocketride-engine image, or by installing the rocketride-mcp Python package from PyPI. The MCP server component connects to the RocketRide runtime engine and exposes its capabilities via the Model Context Protocol.
Which MCP clients work with RocketRide?+
RocketRide works with any MCP-compatible client. The README specifically mentions Claude and Cursor as coding agents that auto-detect RocketRide, and the system integrates with Claude Desktop through the MCP protocol.
Do I need API keys to use RocketRide?+
You'll need API keys for the specific LLM providers and services you configure in your pipelines (e.g., OpenAI, Anthropic, or any of the 15+ supported model providers). The RocketRide engine itself is open source and free to run locally or on-premises under the MIT license.
Is RocketRide free to use?+
Yes, the RocketRide engine and MCP server are fully open source under the MIT license and free for local or on-premises deployment. RocketRide Cloud is a paid managed hosting option that runs the same pipelines without infrastructure overhead.
What are the prerequisites for running RocketRide on-premises?+
For local deployment, install the VS Code extension which bundles the server. For Docker deployment, you need Docker installed to pull the ghcr.io/rocketride-org/rocketride-engine image. All node dependencies, Python environments, and C++ toolchains are managed automatically by the system.
How do I install rocketride-server?+
Open the source repository on GitHub and follow its README. rocketride-server is a mcp server — MCP Agents Market links you directly to the official repo.
Is rocketride-server free?+
rocketride-server is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.