How do I install Dremio MCP server locally?
Clone the repository, install `uv`, ensure Python 3.11+, then run `uv run dremio-mcp-server --help` to verify.
@dremio
基本信息
Dremio MCP server
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"dremio-mcp": {
"command": "docker",
"args": [
"build",
"-t",
"dremio-mcp:0.1.0",
"."
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Dremio MCP server is an MCP (Model Context Protocol) server that enables LLMs to integrate with Dremio for querying, analyzing, and discovering data. It is intended for developers and data professionals who want to use AI assistants like Claude with Dremio.
Install locally using uv and Python 3.11+. Create a Dremio config file with your Dremio URI and PAT (or OAuth), then configure the LLM desktop app (Claude) to reference the server. For production, deploy via Helm chart with streaming HTTP, OAuth, and autoscaling.
Clone the repository, install `uv`, ensure Python 3.11+, then run `uv run dremio-mcp-server --help` to verify.
PAT for development/testing; OAuth with an external token provider for production. A PAT can be stored in a file and referenced with `@` to avoid leaking in shell history.
FOR_DATA_PATTERNS (normal): allows LLM to read tables and data. FOR_SELF: introspects Dremio system, including workload analysis. FOR_PROMETHEUS: connects to Prometheus for Dremio‑related metrics.
Logs are written automatically to platform‑specific directories: `~/.local/share/dremioai/logs/` (Linux), `~/Library/Logs/dremioai/` (macOS), or `%LOCALAPPDATA%\dremioai\logs\` (Windows).
Yes. You must provide a project ID when configuring for Dremio Cloud, and use the URI `https://api.dremio.cloud` (US) or `https://api.eu.dremio.cloud` (EMEA).
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