We are entering a world where most database code will be written by AI agents, not humans. This is already happening. Developers ask Claude, Copilot, or Cursor to write their SQL, and the agent produces something that looks right. For traditional databases, it usually is right.
For streaming databases, it is not.
AI agents have seen billions of lines of batch SQL in their training data. They know PostgreSQL, MySQL, and SQLite inside out. But streaming SQL is different. The semantics are different. The architecture is different. And the mistakes are subtle -- queries that parse and execute correctly but build pipelines that silently duplicate data, miss events, or never produce results.
We decided to fix this at the source. Instead of writing better documentation and hoping agents would find it, we built three tools that meet AI agents where they already work.
The Cloud CLI That Distributes Knowledge
RisingWave Cloud CLI (rwc) started as a straightforward infrastructure tool -- manage clusters, configure auth, take snapshots. But we realized the CLI is the one tool that every RisingWave Cloud user already installs. So we turned it into a distribution channel.
rwc skill install --target claude-code
One command. Your AI coding assistant now understands RisingWave. No repo to clone, no config file to edit, no documentation to bookmark. The knowledge travels with the tool.
This matters because the hardest problem in developer tooling is not building the tool. It is getting it into the developer's workflow. The CLI was already there.
Teaching Agents What LLMs Cannot Learn From Training Data
RisingWave Agent Skills is the knowledge itself -- an open-source pack of structured reference documents that AI agents load into their context window.
Why does this need to exist? Because streaming SQL is a tiny fraction of what LLMs have been trained on. When an agent encounters RisingWave, it pattern-matches against what it knows: batch SQL. And the results are predictable.
It writes CREATE TABLE when it should write CREATE SOURCE. It uses date_trunc when TUMBLE is the right choice. It sets up CDC by creating one table per source, paying the ingestion cost multiple times instead of sharing a single connection. It forgets to set watermarks, and then wonders why time windows never close.
These are not bugs the agent can debug. They are architectural mistakes baked into the first line of code.
The skill pack encodes 14 rules across schema design, materialized views, streaming SQL patterns, sink configuration, and performance optimization. Each rule exists because we have seen the same mistake made by different agents, in different codebases, repeatedly. They follow the open Agent Skills specification and work with Claude Code, Cursor, GitHub Copilot, Windsurf, Gemini CLI, and 18+ other tools.
Giving Agents Eyes Into Your Database
Static knowledge is necessary but not sufficient. An agent that knows the right patterns still cannot see your actual schema, your existing materialized views, or your cluster state.
RisingWave MCP Server bridges this gap. It connects AI agents directly to a running RisingWave instance through the Model Context Protocol, exposing 100+ tools for querying, schema inspection, DDL operations, streaming job monitoring, and cluster management.
The difference is concrete. Without the MCP server, an agent might suggest creating a materialized view that duplicates one you already have. With it, the agent can inspect your existing views, check your source schemas, and write SQL that fits your actual system -- not a hypothetical one.
It integrates with VS Code Copilot and Claude Desktop, and supports both STDIO and HTTP transports.
Three Layers, One Workflow
| Layer | Tool | What it does |
| Infrastructure | rwc CLI | Provisions clusters, manages auth, distributes agent knowledge |
| Knowledge | Agent Skills | Teaches agents correct streaming SQL patterns |
| Live Access | MCP Server | Gives agents real-time visibility into your database |
These tools are independent -- you can use any one without the others. But they are designed to work together. The CLI installs the skills. The skills tell the agent how to think. The MCP server shows the agent what is actually there.
Why This Matters Now
The window for shaping how AI agents write streaming SQL is right now. Patterns established today will be reinforced in every future codebase these agents touch. If agents learn the wrong patterns, those patterns will propagate. If they learn the right ones, every developer who uses an AI assistant gets the benefit.
We are building these tools because we believe the quality of AI-generated streaming code should not depend on the developer's expertise in streaming systems. The agent should know what to do. That is the standard we are working toward.
All three tools are open source and free to use:
- Cloud CLI -- install
rwcand get started - Agent Skills -- teach your AI assistant streaming SQL
- MCP Server -- connect your agent to a live instance
FAQ
Do I need RisingWave Cloud to use these tools?
Only the rwc CLI requires a Cloud account. Agent Skills and the MCP Server work with any RisingWave deployment, including open-source self-hosted.
Which AI coding assistants are supported? Agent Skills work with Claude Code, Cursor, GitHub Copilot, Windsurf, Gemini CLI, and 18+ other tools. The MCP Server works with any MCP-compatible client.
Can I contribute to the agent skills? Yes. Both the Agent Skills and MCP Server repos are open source. We welcome contributions from the community.
