Milvus for AI Agents
Milvus provides agent-friendly interfaces that allow AI coding agents and autonomous agent systems to interact with vector databases programmatically. Whether you are building RAG pipelines, semantic search, or agent memory systems, Milvus offers multiple ways for agents to connect and operate.
Agent tools
AI prompts
Curated prompts that help AI coding assistants write correct Milvus code. Each prompt encodes the rules and patterns that prevent the most common mistakes.
How to use:
- Copy a prompt from the “Full prompt” section on any prompt page.
- Save it to the file your AI tool expects (see environments table below).
- Your AI assistant will automatically apply the rules when it generates or reviews Milvus code.
Prompt pages
Use in different environments
| Environment | Where to put prompt | Instructions |
|---|---|---|
| Cursor | .cursor/rules/*.md | Configure project rules |
| GitHub Copilot | .github/copilot-instructions.md | Custom instructions |
| Claude Code | CLAUDE.md | Claude Code docs |
| JetBrains IDEs | guidelines.md | Customize guidelines |
| Gemini CLI | GEMINI.md | Gemini CLI codelab |
| VS Code | .instructions.md | Configure .instructions.md |
| Windsurf | guidelines.md | Configure guidelines.md |
Recommended deployment for agents
Choosing the right Milvus deployment depends on your development stage.
| Stage | Deployment | Why |
|---|---|---|
| Prototyping | Milvus Lite | Zero-config, in-process. Runs anywhere Python runs — ideal for rapid agent prototyping. |
| Development | Milvus Standalone | Single-node Docker deployment. Good for local development and testing with realistic data volumes. |
| Production | Zilliz Cloud | Fully managed, serverless Milvus. No infrastructure to manage — agents just connect and operate. |
| Self-hosted production | Milvus Distributed | Multi-node Kubernetes deployment for teams that need full control over their infrastructure. |
For agent workloads, Zilliz Cloud is recommended for production use. Agents typically do not manage infrastructure, so a serverless deployment eliminates operational overhead and provides automatic scaling.