An MCP server that exposes NetApp AI Data Engine's RAG search API through a local stdio MCP interface. It lets clients search for documents using semantic similarity over AIDE's vector-based retrieval system.
From the registry: MCP server for NetApp AI Data Engine
$ chmod 600 ~/.netappPlease install the `aide-mcp-server` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Install Python 3.10+** — Python 3.10 or newer is required to run the server via uvx.
- **Install uv** — Install uv, which manages running the package automatically. (https://docs.astral.sh/uv/)
- **Create NetApp configuration file** — Create a .netapp file in your home directory containing the NetApp AI Data Engine RAG API and authentication settings. The server reads authentication and endpoint configuration from this file rather than MCP env vars.
Optional prerequisites:
- Restrict .netapp file permissions — Ensure the .netapp file is not readable by other users. On Unix-like systems, use chmod 600 ~/.netapp. Run: `chmod 600 ~/.netapp`
Canonical MCP server config (stdio transport):
- command: `uvx`
- args: ["--from","netapp-aide-mcp","server"]
Note: This is a local stdio MCP server. Authentication is initiated on the first tool call, not at server startup. No MCP config env vars are documented; required endpoint and auth settings must be placed in ~/.netapp. Supported auth flows in ~/.netapp are PKCE and device code.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.MCP server for searching Airweave collections with natural language queries.