Supabase
Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.
Description from the maker (original English)
Query ClickHouse over HTTP: list databases and tables, run SELECT.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"analyticbase": {
"command": "npx",
"args": [
"-y",
"@reneturcios/analyticbase",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add analyticbase -- npx -y @reneturcios/analyticbase mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"analyticbase": {
"command": "npx",
"args": [
"-y",
"@reneturcios/analyticbase",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"analyticbase": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/analyticbase",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account CloudCorpRecords, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 6 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.
In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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.