Supabase
MCP server for interacting with the Supabase platform
作者提供的说明(英文原文)
Query ClickHouse over HTTP: list databases and tables, run SELECT.
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。
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": {
"analyticbase": {
"command": "npx",
"args": [
"-y",
"@reneturcios/analyticbase",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add analyticbase -- npx -y @reneturcios/analyticbase mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"analyticbase": {
"command": "npx",
"args": [
"-y",
"@reneturcios/analyticbase",
"mcp"
]
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"analyticbase": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/analyticbase",
"mcp"
]
}
}
}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。
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6日
注册名称已通过 GitHub 账户 CloudCorpRecords 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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
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(0.1.0)于6天前进入注册中心。
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 Node.js, Docker。
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。
analyticbase lets an agent — or you, at a terminal — look inside a ClickHouse database and ask it questions, without ever being able to change it. It lists the databases on a server, lists the tables in one database along with each table's engine, comment, row count and column count, and runs single read-only SELECT queries. Everything travels over ClickHouse's plain HTTP interface, so there is no client library bundled and no native port to tunnel.
When ClickHouse is not there, analyticbase says so. The MCP server starts and lists its tools with no server behind it at all; only an actual operation makes a request, and a refused connection or a server error comes back as an error carrying the server's own text — never as invented rows.
npx @reneturcios/analyticbase list-databases
Or run the container image:
docker run -i ghcr.io/cloudcorprecords/analyticbase
The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.
# Which databases does this server hold?
analyticbase list-databases
analyticbase list-tables analytics analyticbase list-tables analytics --like "events_%" --not-like "%_tmp"
analyticbase query "SELECT count() AS n FROM analytics.events"
analyticbase mcp
analyticbase --version
Exit codes: 0 on success, 1 when the query, the guard, or the connection fails (the error says which), 2 for usage errors.
The endpoint is configured through the environment:
| Variable | Meaning | Default |
|---|---|---|
CLICKHOUSE_URL | Whole base URL of the HTTP interface; overrides host and port | — |
CLICKHOUSE_HOST | Hostname, or a full http(s):// URL | localhost |
CLICKHOUSE_PORT | HTTP interface port | 8123 |
CLICKHOUSE_USER | Username | default |
CLICKHOUSE_PASSWORD | Password | (empty) |
Each operation POSTs its SQL to the HTTP interface as the request body, with the credentials as URL parameters — the interface's own convention. The listing operations append FORMAT JSONEachRow and parse one JSON object per line; list_tables reads system.tables and counts each table's columns with a subquery over system.columns, applying the like / not_like filters as LIKE / NOT LIKE clauses with safely escaped literals. Select queries append FORMAT JSON and return the response's data array.
run_select_query (and the CLI query command) accepts a query only if all of these hold:
SELECT or WITH.INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, TRUNCATE, GRANT, REVOKE, OPTIMIZE, RENAME, DETACH, or ATTACH appears as a whole word outside a string literal. Single-quoted literals are blanked out before scanning, so SELECT 'drop table t' is a fine query; a column literally named update is not — the guard would rather refuse an odd name than be talked around.The listing operations build their SQL internally from validated, escaped pieces, so they need no guard.
One bin serves both faces. The mcp subcommand starts a stdio MCP server:
npx -y @reneturcios/analyticbase mcp
MCP client configuration:
{
"mcpServers": { "analyticbase": { "command": "npx", "args": ["-y", "@reneturcios/analyticbase", "mcp"], "env": { "CLICKHOUSE_HOST": "localhost", "CLICKHOUSE_PORT": "8123" } } } }
| Tool | Input | What it returns |
|---|---|---|
list_databases | (none) | One object per database, from system.databases. |
list_tables | database (string, required), like / not_like (strings, optional) | One object per table in that database: its schema (database), name, engine, comment, row count, and column count. |
run_select_query | query (string, required) — one read-only SQL statement | The result rows as a JSON array of objects keyed by column name. Guard violations, a missing server, and database errors all come back as tool errors — never as made-up rows. |
npm install
npm run build # tsc -> dist/ npm test # node test runner over test/*.test.ts, no network, no live ClickHouse npm run dev # run the CLI from source via tsx
All HTTP goes through an injectable fetch function, which is what the test suite drives: config resolution, the guard, SQL construction, both response-format parsers, and all three operations are covered against a fake fetch.
MIT — see LICENSE.