HTTP MCP Server

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HTTP MCP Server

The RocketRide engine has a built-in MCP server — nothing to install, nothing to run. Connect an AI assistant to it and the assistant can build, validate, run, and observe RocketRide pipelines, manage deployments, and read your account file store.

Endpoint

https://api.rocketride.ai/mcp

Self-hosted engines serve the same endpoint automatically at http://<host>:5565/mcp as soon as the engine is up (see Self-hosting).

Authentication

Clients like Claude and ChatGPT authenticate with OAuth — the first connection triggers an interactive login, and users without a RocketRide account can sign up from the same screen. Header-capable clients (Cursor, scripts, CLIs) can instead send a RocketRide API key: Authorization: Bearer rr_....

Task-scoped keys (tk_/pk_) are never accepted on this endpoint. Setup steps for each client are on Connect a client.

What you can do

The server exposes 29 tools, organized by capability — the full parameter-level reference is on Tools:

Capability	Tools
Discover components	list_components, describe_component, resolve_config, list_integrations
Author pipelines	validate_pipeline, describe_pipeline, scaffold_node, save_template, load_template
Run pipelines	run_pipeline, run_dropper_pipe, send_data, send_files, terminate
Watch what's running	monitor, list_running_pipelines
Read the file store	store_read, store_list, store_stat, store_get_url
Manage deployments	deploy_add, deploy_list, deploy_status, deploy_remove, deploy_update
Replay past runs	log_chapters, log_read, log_traces, log_trace

Two things to know when working with the tools:

• Pipelines travel inline. No tool accepts a pipeline filepath — a client that has a .pipe file reads it itself and sends the JSON.
• Files come in over a separate channel. run_dropper_pipe returns an upload_url for programmatic uploads and a dropper_url — a browser page where a person can drag and drop files into the running pipeline.

Example prompts

Build and run a pipeline that summarizes the PDFs I upload.

Which components can I use right now without setting up any credentials?

Show me what happened in my last run — where did the second document fail?

Deploy this pipeline to run every night at 2am.

Security model

• Inline-only pipelines — no tool accepts a server-local pipeline path, so a caller can never make the engine read pipeline definitions off its own disk.
• Store-scoped reads — the four store_* tools resolve paths through your account's file store on the engine, nothing else. (send_files is the one exception: its paths resolve on the machine the engine runs on — see its reference entry.)
• Credential names, never values — integration-readiness tools report which environment variables are configured; the values never transit MCP.
• Audience-enforced OAuth — tokens must be minted for this resource; task-scoped keys and PKCE codes are rejected outright.
• Per-caller identity — every request acts as the account behind the presented credential; tools see that caller's own store, deployments, and environment.

Explore

Connect a clientSetup for Claude, Claude Code, Cursor, and VS Code; OAuth and API-key auth; transport details.ToolsAll 29 tools with parameters, return shapes, and the error contract.Resources & WidgetsLive MCP resources and the interactive widgets rendered in MCP Apps hosts.Self-hostingOAuth configuration, environment variables, and the dev-mode auth bypass.

Looking for the stdio PyPI package (rocketride-mcp) that exposes running pipelines as tools instead? That's the stdio MCP server.