Supabase
MCP server for interacting with the Supabase platform
作者提供的说明(英文原文)
MCP Server for Snowflake from Snowflake Labs
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
SNOWFLAKE_ACCOUNT, SNOWFLAKE_HOST, SNOWFLAKE_USER, SNOWFLAKE_PASSWORD, SNOWFLAKE_ROLE, SNOWFLAKE_WAREHOUSE, SNOWFLAKE_PASSCODE, SNOWFLAKE_PRIVATE_KEY, SNOWFLAKE_PRIVATE_KEY_FILE, SNOWFLAKE_PRIVATE_KEY_FILE_PWD, SNOWFLAKE_MCP_HOST, SNOWFLAKE_MCP_PORT, SNOWFLAKE_MCP_ENDPOINT标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"snowflake-labs": {
"command": "uvx",
"args": [
"snowflake-labs-mcp",
"--service-config-file",
"your-value",
"--authenticator",
"snowflake",
"--transport",
"stdio",
"--server-host",
"0.0.0.0",
"--port",
"9000",
"--endpoint",
"/mcp"
],
"env": {
"SNOWFLAKE_ACCOUNT": "your-value",
"SNOWFLAKE_HOST": "your-value",
"SNOWFLAKE_USER": "your-value",
"SNOWFLAKE_PASSWORD": "your-value",
"SNOWFLAKE_ROLE": "your-value",
"SNOWFLAKE_WAREHOUSE": "your-value",
"SNOWFLAKE_PASSCODE": "your-value",
"SNOWFLAKE_PRIVATE_KEY": "your-value",
"SNOWFLAKE_PRIVATE_KEY_FILE": "your-value",
"SNOWFLAKE_PRIVATE_KEY_FILE_PWD": "your-value",
"SNOWFLAKE_MCP_HOST": "your-value",
"SNOWFLAKE_MCP_PORT": "your-value",
"SNOWFLAKE_MCP_ENDPOINT": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add snowflake-labs --env SNOWFLAKE_ACCOUNT=your-value --env SNOWFLAKE_HOST=your-value --env SNOWFLAKE_USER=your-value --env SNOWFLAKE_PASSWORD=your-value --env SNOWFLAKE_ROLE=your-value --env SNOWFLAKE_WAREHOUSE=your-value --env SNOWFLAKE_PASSCODE=your-value --env SNOWFLAKE_PRIVATE_KEY=your-value --env SNOWFLAKE_PRIVATE_KEY_FILE=your-value --env SNOWFLAKE_PRIVATE_KEY_FILE_PWD=your-value --env SNOWFLAKE_MCP_HOST=your-value --env SNOWFLAKE_MCP_PORT=your-value --env SNOWFLAKE_MCP_ENDPOINT=your-value -- uvx snowflake-labs-mcp --service-config-file your-value --authenticator snowflake --transport stdio --server-host 0.0.0.0 --port 9000 --endpoint /mcp运行前请先填写空着的值。
这个服务器需要在启动命令中填入值,请复制设置后自行填写。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"snowflake-labs": {
"command": "uvx",
"args": [
"snowflake-labs-mcp",
"--service-config-file",
"your-value",
"--authenticator",
"snowflake",
"--transport",
"stdio",
"--server-host",
"0.0.0.0",
"--port",
"9000",
"--endpoint",
"/mcp"
],
"env": {
"SNOWFLAKE_ACCOUNT": "your-value",
"SNOWFLAKE_HOST": "your-value",
"SNOWFLAKE_USER": "your-value",
"SNOWFLAKE_PASSWORD": "your-value",
"SNOWFLAKE_ROLE": "your-value",
"SNOWFLAKE_WAREHOUSE": "your-value",
"SNOWFLAKE_PASSCODE": "your-value",
"SNOWFLAKE_PRIVATE_KEY": "your-value",
"SNOWFLAKE_PRIVATE_KEY_FILE": "your-value",
"SNOWFLAKE_PRIVATE_KEY_FILE_PWD": "your-value",
"SNOWFLAKE_MCP_HOST": "your-value",
"SNOWFLAKE_MCP_PORT": "your-value",
"SNOWFLAKE_MCP_ENDPOINT": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器需要在启动命令中填入值,请复制设置后自行填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"snowflake-labs": {
"type": "stdio",
"command": "uvx",
"args": [
"snowflake-labs-mcp",
"--service-config-file",
"your-value",
"--authenticator",
"snowflake",
"--transport",
"stdio",
"--server-host",
"0.0.0.0",
"--port",
"9000",
"--endpoint",
"/mcp"
],
"env": {
"SNOWFLAKE_ACCOUNT": "your-value",
"SNOWFLAKE_HOST": "your-value",
"SNOWFLAKE_USER": "your-value",
"SNOWFLAKE_PASSWORD": "your-value",
"SNOWFLAKE_ROLE": "your-value",
"SNOWFLAKE_WAREHOUSE": "your-value",
"SNOWFLAKE_PASSCODE": "your-value",
"SNOWFLAKE_PRIVATE_KEY": "your-value",
"SNOWFLAKE_PRIVATE_KEY_FILE": "your-value",
"SNOWFLAKE_PRIVATE_KEY_FILE_PWD": "your-value",
"SNOWFLAKE_MCP_HOST": "your-value",
"SNOWFLAKE_MCP_PORT": "your-value",
"SNOWFLAKE_MCP_ENDPOINT": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
SNOWFLAKE_ACCOUNT envSNOWFLAKE_HOST envSNOWFLAKE_USER envSNOWFLAKE_ROLE envSNOWFLAKE_WAREHOUSE envSNOWFLAKE_PASSCODE envSNOWFLAKE_PRIVATE_KEY_FILE envSNOWFLAKE_PRIVATE_KEY_FILE_PWD envSNOWFLAKE_MCP_HOST envSNOWFLAKE_MCP_PORT envSNOWFLAKE_MCP_ENDPOINT env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 Snowflake-Labs 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:SNOWFLAKE_PASSWORD, SNOWFLAKE_PRIVATE_KEY
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.3.5)于12个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Supabase, MongoDB MCP Server, Elasticsearch MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP server for interacting with the Supabase platform
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
[!CAUTION]
This project is deprecated and no longer maintained. Please migrate to the official Snowflake MCP Server. The official server is actively developed, fully supported by Snowflake, and continues to add new features.
This community MCP server previously provided tooling for Snowflake Cortex AI, object management, and SQL orchestration. It is no longer supported. For all new and existing use cases, please use the official Snowflake MCP Server instead.
Legacy documentation (for reference only)
The MCP server supported the below capabilities:
A simple configuration file is used to drive all tooling. An example can be seen at services/configuration.yaml and a template is below. The path to this configuration file will be passed to the server and the contents used to create MCP server tools at startup.
Cortex Services
Many Cortex Agent, Search, and Analyst services can be added. Ideal descriptions are both highly descriptive and mutually exclusive. Only the explicitly listed Cortex services will be available as tools in the MCP client.
Other Services
Other services include tooling for object management, query execution, and semantic view usage. These groups of tools can be enabled by setting them to True in the other_services section of the configuration file.
SQL Statement Permissions
The sql_statement_permissions section ensures that only approved statements are executed across any tools with access to change Snowflake objects. The list contains SQL expression types. Those marked with True are permitted while those marked with False are not permitted. Please see SQL Execution for examples of each expression type.
agent_services: # List all Cortex Agent services
database_name: schema_name:
database_name: schema_name: search_services: # List all Cortex Search services
database_name: schema_name:
database_name: schema_name: analyst_services: # List all Cortex Analyst semantic models/views
other_services: # Set desired tool groups to True to enable tools for that group object_manager: True # Perform basic operations against Snowflake's most common objects such as creation, dropping, updating, and more. query_manager: True # Run LLM-generated SQL managed by user-configured permissions. semantic_manager: True # Discover and query Snowflake Semantic Views and their components. sql_statement_permissions: # List SQL statements to explicitly allow (True) or disallow (False).
[!NOTE]
Previous versions of the configuration file supported specifying explicit values for columns and limit for each Cortex Search service. Instead, these are now exclusively dynamic based on user prompt. If not specified, a search service's default search_columns will be returned with a limit of 10.
The MCP server uses the Snowflake Python Connector for all authentication and connection methods. Please refer to the official Snowflake documentation for comprehensive authentication options and best practices.
The MCP server honors the RBAC permissions assigned to the specified role (as passed in the connection parameters) or default role of the user (if no role is passed to connect).
Connection parameters can be passed as CLI arguments and/or environment variables. The server supports all authentication methods available in the Snowflake Python Connector, including:
Connection parameters can be passed as CLI arguments and/or environment variables:
| Parameter | CLI Arguments | Environment Variable | Description |
|---|---|---|---|
| Account | --account | SNOWFLAKE_ACCOUNT | Account identifier (e.g. xy12345.us-east-1) |
| Host | --host | SNOWFLAKE_HOST | Snowflake host URL |
| User | --user, --username | SNOWFLAKE_USER | Username for authentication |
| Password | --password | SNOWFLAKE_PASSWORD | Password or programmatic access token |
| Role | --role | SNOWFLAKE_ROLE | Role to use for connection |
| Warehouse | --warehouse | SNOWFLAKE_WAREHOUSE | Warehouse to use for queries |
| Passcode in Password | --passcode-in-password | - | Whether passcode is embedded in password |
| Passcode | --passcode | SNOWFLAKE_PASSCODE | MFA passcode for authentication |
| Private Key | --private-key | SNOWFLAKE_PRIVATE_KEY | Private key for key pair authentication |
| Private Key File | --private-key-file | SNOWFLAKE_PRIVATE_KEY_FILE | Path to private key file |
| Private Key Password | --private-key-file-pwd | SNOWFLAKE_PRIVATE_KEY_FILE_PWD | Password for encrypted private key |
| Authenticator | --authenticator | - | Authentication type (default: snowflake) |
| Connection Name | --connection-name | - | Name of connection from connections.toml (or config.toml) file |
[!WARNING]
Deprecation Notice: The CLI arguments
--account-identifierand--pat, as well as the environment variableSNOWFLAKE_PAT, are deprecated and will be removed in a future release. Please use--accountand--password(orSNOWFLAKE_ACCOUNTandSNOWFLAKE_PASSWORD) instead.
The MCP server supports multiple transport mechanisms. For detailed information about MCP transports, see FastMCP Transport Protocols.
| Transport | Description | Use Case |
|---|---|---|
stdio | Standard input/output (default) | Local development, MCP client integration |
sse (legacy) | Server-Sent Events | Streaming applications |
streamable-http | Streamable HTTP transport | Container deployments, remote servers |
# Default stdio transport
uvx snowflake-labs-mcp --service-config-file config.yaml
uvx snowflake-labs-mcp --service-config-file config.yaml --transport streamable-http --endpoint /my-endpoint
uvx snowflake-labs-mcp --service-config-file config.yaml --transport streamable-http --endpoint /snowflake-mcp
Server customizations available for sse and streamable-http transports:
| Parameter | CLI Argument | Environment Variable | Default |
|---|
| Host | --server-host | SNOWFLAKE_MCP_HOST | "0.0.0.0" | Port | --port | SNOWFLAKE_MCP_PORT | 9000 | Endpoint | --endpoint | SNOWFLAKE_MCP_ENDPOINT | /mcp | Debug Logging | --verbose | SNOWFLAKE_MCP_VERBOSE | false
Example:
export SNOWFLAKE_MCP_ENDPOINT="/my-mcp"
uvx snowflake-labs-mcp --service-config-file config.yaml --transport streamable-http
The MCP server is client-agnostic and will work with most MCP Clients that support basic functionality for MCP tools and (optionally) resources. Below are examples for local installation. For connecting to containerized deployments, see Connecting MCP Clients to Containers.
To integrate this server with Claude Desktop as the MCP Client, add the following to your app's server configuration. By default, this is located at:
Set the path to the service configuration file and configure your connection method:
{
"mcpServers": { "mcp-server-snowflake": { "command": "uvx", "args": [ "snowflake-labs-mcp", "--service-config-file", " /tools_config.yaml", "--connection-name", "default" ] } } }
Register the MCP server in Cursor by opening Cursor and navigating to Settings -> Cursor Settings -> MCP. Add the below:
{
"mcpServers": { "mcp-server-snowflake": { "command": "uvx", "args": [ "snowflake-labs-mcp", "--service-config-file", " /tools_config.yaml", "--connection-name", "default" ] } } }
Add the MCP server as context in the chat.
For troubleshooting Cursor server issues, view the logs by opening the Output panel and selecting Cursor MCP from the dropdown menu.
Update the fastagent.config.yaml mcp server section with the configuration file path and connection name:
# MCP Servers
mcp: servers: mcp-server-snowflake: command: "uvx" args: ["snowflake-labs-mcp", "--service-config-file", " /tools_c
只显示了开头部分;其余内容请在仓库中阅读