Supabase
MCP server for interacting with the Supabase platform
作者による説明(英語の原文)
MCP server for database connectivity. Multi-DB (PostgreSQL, MySQL, SQLite), 19 tools.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"database": {
"command": "npx",
"args": [
"-y",
"@cocaxcode/database-mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add database -- npx -y @cocaxcode/database-mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"database": {
"command": "npx",
"args": [
"-y",
"@cocaxcode/database-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"database": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@cocaxcode/database-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント cocaxcode で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.1.14)がレジストリに届いたのは8 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:Supabase, MongoDB MCP Server, Elasticsearch MCP Server
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
MCP server for interacting with the Supabase platform
MongoDB Model Context Protocol Server
MCP server for interacting with Elasticsearch
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
@cocaxcode/database-mcp
Your databases, one conversation away.
33 tools · PostgreSQL · MySQL · SQLite · Connection Groups · Rollback · Dump/Restore · Schema auto-discovery
Overview · Just Talk to It · Connection Groups · Installation · Features · Tool Reference · Storage · Architecture
The most complete MCP server for databases. 33 tools across 3 engines (PostgreSQL, MySQL, SQLite), with connection groups, named connection management, automatic rollback, dump/restore, schema auto-discovery via MCP Resources, and full query history — all from natural language.
This is not just a query runner. It is a full database workbench: organize connections into groups scoped to your project directories, set defaults that persist between sessions, introspect schemas at three levels of detail, get pre-mutation snapshots on every write, undo mistakes with reverse SQL, dump and restore entire databases, and track every query you run — per project, per connection.
Every connection belongs to a group. Groups have scopes (directories), a default connection, and an active connection. When you work inside a scoped directory, you only see that group's connections — no clutter, no confusion.
You describe what you need. The AI reads your schema, writes the SQL, and executes it safely — with automatic LIMIT injection, pre-mutation snapshots, and confirmation before destructive operations. No cloud accounts, no ORMs, no config files. Credentials never leave your machine. Everything runs locally.
Works with Claude Code, Claude Desktop, Cursor, Windsurf, VS Code, Codex CLI, Gemini CLI, and any MCP-compatible client.
You don't need to memorize tool names or SQL syntax. Just say what you want.
> "Connect to my local PostgreSQL on port 5432, database myapp, user admin"
"Create a group called backend and add this directory"
"Connect to my PostgreSQL on localhost, put it in the backend group"
"Set local-pg as the default connection"
"Show me all tables"
"What columns does the users table have?"
"Show me the last 10 orders with the customer name"
-> AI reads FKs from schema, builds the JOIN, applies LIMIT 10
"Insert a test user called Alice"
-> Snapshot captured for rollback
"Oops, undo that"
-> Rows restored via reverse SQL
"Switch to the production database for this session"
-> Instant context change, all queries now go to prod
"Delete all inactive users"
-> "This will affect N rows. Call again with confirm=true to proceed."
"What did I run today?"
-> Full query history with timestamps and execution times
"Dump the database — structure and data"
-> SQL file generated, ready for restore
The AI already knows your schema through MCP Resources. It reads db://schema to discover tables and db://tables/{name}/schema for columns, foreign keys, and indexes. When you ask for data across tables, it builds correct JOINs automatically.
Every connection belongs to a group. Groups are the organizing unit for your database connections — they keep things scoped, clean, and automatic.
A group has three key concepts:
Here is a practical workflow:
"Create a group called backend"
"Add this directory as scope" "Create a PostgreSQL connection called local-dev in the backend group" <- auto-default (first connection) "Create another called production in backend" "List connections" <- shows local-dev (active, default) "Switch to production" <- session only "Set production as default" <- persists between sessions
The first connection added to a group becomes the default automatically. Switching connections only changes the active for the current session — restart and you are back to the default. If you want the change to stick, set a new default explicitly.
This means you can safely switch to production for a quick query and know that next time you open the project, you will be back on your development database.
claude mcp add --scope user database -- npx -y @cocaxcode/database-mcp@latest
Add to your config file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows):
{
"mcpServers": { "database": { "command": "npx", "args": ["-y", "@cocaxcode/database-mcp@latest"] } } }
Cursor / Windsurf
Add to .cursor/mcp.json or .windsurf/mcp.json in your project root:
{
"mcpServers": { "database": { "command": "npx", "args": ["-y", "@cocaxcode/database-mcp@latest"] } } }
</details>
VS Code
Add to .vscode/mcp.json:
{
"servers": { "database": { "type": "stdio", "command": "npx", "args": ["-y", "@cocaxcode/database-mcp@latest"] } } }
</details>
Codex CLI (OpenAI)
codex mcp add database -- npx -y @cocaxcode/database-mcp@latest
Or add to ~/.codex/config.toml:
[mcp_servers.database]
command = "npx" args = ["-y", "@cocaxcode/database-mcp@latest"]
</details>
Gemini CLI (Google)
Add to ~/.gemini/settings.json:
{
"mcpServers": { "database": { "command": "npx", "args": ["-y", "@cocaxcode/database-mcp@latest"] } } }
</details>
Install only the driver(s) you need — they load dynamically at runtime:
npm install -g postgres # PostgreSQL (postgres.js)
npm install -g mysql2 # MySQL npm install -g sql.js # SQLite (runs in-process, no native bindings)
Note: When using
npx, drivers must be installed globally. If you install the server globally (npm install -g @cocaxcode/database-mcp), drivers can be local or global.
Most database MCP servers make you reconfigure credentials every session. This one does not. Named connections persist inside groups — create them once, use them forever.
Named connections work like git branches. You create dev, staging, prod once inside a group and they are always there. Switching is instant — one command, zero reconfiguration:
"Create a group called my-project and add this directory as scope"
"Create a connection called dev with host localhost, database myapp, user admin in my-project" "Create a read-only connection called analytics pointing to ./data/metrics.db in my-project" "Switch to dev" -> queries go to PostgreSQL "Switch to analytics" -> queries go to SQLite "Duplicate dev as dev-readonly with read-only mode"
Group-scoped connections mean different projects see different databases automatically. Working on project A? You see project A's group and connections. Switch to project B's directory and it picks up project B's group with its own default. No manual switching, no interference between projects:
"Create a group called frontend with scope /home/user/frontend"
"Create a group called backend with scope /home/user/backend"
Now each directory has its own isolated set of connections.
100% local credentials. Every connection is stored as a JSON file in ~/.database-mcp/connections/. Passwords never leave your machine. Nothing is sent to the cloud. Nothing is committed to git. Your credentials are yours.
Live management. Create, duplicate, rename, test, export, and switch connections mid-conversation. No restart needed, no config file editing, no context loss.
| Protection | How it works |
|---|---|
| Read-only mode | Connection-level enforcement — blocks all mutations |
| Confirmation required | Destructive ops require explicit confirm: true |
| Auto LIMIT | Read queries get LIMIT 100 by default (respects existing LIMIT) |
| Password masking | Credentials shown as *** in conn_get output |
| Pre-mutation snapshots | Every INSERT/UPDATE/DELETE captures row state for rollback |
| Auto gitignore | .database-mcp/ added to .gitignore on first write |
Every mutation captures a pre-state snapshot. Undo anything.
"Show me available rollbacks"
"Rollback the last delete" -> "This will INSERT 47 rows back into orders. Confirm?" -> Rows restored via reverse SQL
| Original operation | Rollback generates |
|---|---|
DELETE WHERE id = 5 | INSERT INTO ... VALUES (...) |
UPDATE SET name = 'Bob' | UPDATE SET name = 'Alice' (pre-update values) |
INSERT INTO ... | DELETE WHERE id = {new_id} |
| DDL (CREATE, ALTER, DROP) | Logged but not reversible |
Three levels of detail, with pattern filtering:
"List all tables" -> names only (fast)
"Show me the users table with columns" -> columns + types + nullable "Full schema for orders including FKs" -> columns + foreign keys + indexes "Tables starting with user" -> pattern: 'user%'
MCP Resources (db://schema and db://tables/{name}/schema) give AI agents automatic access to your schema — no manual SQL needed for multi-table queries.
"Show me all users"
-> SELECT * FROM users LIMIT 100 <- auto LIMIT
"Show the execution plan for this query" -> EXPLAIN ANALYZE with dialect-specific syntax (PostgreSQL/MySQL/SQLite)
SQL results often carry TEXT / JSON / HTML columns that can be kilobytes per row. AI agents pay for every byte that reaches the context window. execute_query, execute_mutation and explain_query accept four optional parameters that cut 60-95% of those tokens while keeping rows and structure intact.
| Param | Values | What it does |
|---|---|---|
verbosity | 'minimal' / 'normal' (default) / 'full' | Controls detail level |
only_columns | ['id', 'title'] | Returns only these columns (client-side projection) |
| max_cell_bytes | number (default 500) | Per-cell byte cap for `'nor
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