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)
Execute SQL and inspect tables, views, schemas and more on a configured database.
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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": {
"databridge-kit": {
"command": "npx",
"args": [
"-y",
"@reneturcios/databridge-kit",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add databridge-kit -- npx -y @reneturcios/databridge-kit mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"databridge-kit": {
"command": "npx",
"args": [
"-y",
"@reneturcios/databridge-kit",
"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": {
"databridge-kit": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/databridge-kit",
"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.
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databridge-kit is a small bridge between an agent (or a terminal) and one configured PostgreSQL database. It can run a single SQL statement and answer the seven inspection questions that come up constantly while exploring an unfamiliar database: which tables, views, schemas, triggers, indexes, sequences and stored procedures exist.
The toolset mirrors the documented prebuilt Postgres toolset of a config-defined database toolbox: the tools are fixed, the database is whatever the connection string points at. There is no bundled database driver — statements run through the psql command-line client, so a machine that wants live answers needs psql on its PATH. Without it — or without a connection string — the server still starts and lists its tools; only the calls themselves report the problem.
npx @reneturcios/databridge-kit list-tables postgres://user@localhost:5432/mydb
Or run the container image:
docker run -i ghcr.io/cloudcorprecords/databridge-kit
The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.
# Run one SQL statement; rows print as JSON
databridge-kit execute-sql postgres://alice@localhost/shop "SELECT id, name FROM products ORDER BY id"
databridge-kit list-tables postgres://alice@localhost/shop databridge-kit list-views postgres://alice@localhost/shop databridge-kit list-schemas postgres://alice@localhost/shop databridge-kit list-triggers postgres://alice@localhost/shop databridge-kit list-indexes postgres://alice@localhost/shop databridge-kit list-sequences postgres://alice@localhost/shop databridge-kit list-stored-procedures postgres://alice@localhost/shop
databridge-kit mcp postgres://alice@localhost/shop
databridge-kit --version
Exit codes: 0 on success, 1 when the statement, the connection string, or psql itself fails (the error says which), 2 for usage errors.
The connection string is a normal PostgreSQL URL: postgres:// or postgresql://, with host, optional port (default 5432), database name from the path, and optional user and password in the userinfo. For the mcp command the string can be left off the command line and supplied through the DATABRIDGE_DATABASE_URL environment variable instead (plain DATABASE_URL works too).
execute_sql accepts exactly one statement per call. Semicolons inside string literals and comments do not count as statement boundaries, but a second real statement is rejected before anything reaches the database. The statement type is not restricted — this is a general bridge, so a caller who can reach it can write as well as read; point it only at databases where that is intended.
Each inspection tool runs one fixed catalogue query:
| Tool | Catalogue read |
|---|---|
list_tables | information_schema.tables (base tables) |
list_views | information_schema.views |
list_schemas | information_schema.schemata |
list_triggers | information_schema.triggers |
list_indexes | pg_indexes |
list_sequences | information_schema.sequences |
list_stored_procedure | information_schema.routines |
Statements run as psql -v ON_ERROR_STOP=1 --csv -c and the CSV output is parsed into row objects. Values come back as the strings psql rendered.
One bin serves both faces. The mcp subcommand starts a stdio MCP server:
npx -y @reneturcios/databridge-kit mcp postgres://alice@localhost/shop
MCP client configuration:
{
"mcpServers": { "databridge-kit": { "command": "npx", "args": ["-y", "@reneturcios/databridge-kit", "mcp"], "env": { "DATABRIDGE_DATABASE_URL": "postgres://alice@localhost/shop" } } } }
| Tool | Input | What it returns |
|---|---|---|
execute_sql | sql (string, required) — one SQL statement | The result rows as a JSON array of objects keyed by column name. |
list_tables | — | Rows describing the base tables in the configured source. |
list_views | — | Rows describing the views in the configured source. |
list_schemas | — | Rows describing the schemas in the configured source. |
list_triggers | — | Rows describing the triggers in the configured source. |
list_indexes | — | Rows describing the indexes in the configured source. |
list_sequences | — | Rows describing the sequences in the configured source. |
list_stored_procedure | — | Rows describing the stored procedures (routines) in the configured source. |
A missing connection, a missing psql, a multi-statement execute_sql, 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 database npm run dev # run the CLI from source via tsx
The core logic sits behind an injectable executor interface, which is what the test suite drives: connection-string parsing, the single-statement check, pass-through execution, error propagation, and the exact catalogue SQL behind every inspection tool are all covered with a fake executor.
MIT — see LICENSE.