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)
Read-only SQL across your PostgreSQL, MySQL, S3 buckets and local data files, in one query.
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
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Download the maker’s .mcpb file
The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.
Run this in your terminal
claude mcp add streams -- npx -y @dbconvert/stream-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"streams": {
"command": "npx",
"args": [
"-y",
"@dbconvert/stream-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": {
"streams": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@dbconvert/stream-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.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
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 against the domain dbconvert.com (the registry checks domain ownership)
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 (2.7.3) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB, Docker, Node.js 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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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.
Database IDE + migration + real-time CDC — in one workflow.
Query data,
move it,
keep it in sync,
and let your AI assistant see it all
without switching between tools.
If this looks useful, consider giving it a ⭐
Most setups look like this:
It works, but it's fragmented.
DBConvert Streams combines these into one workspace.
Think of it as:
DBeaver / DataGrip
but without switching tools every time
Run queries across databases and files:
SELECT *
FROM read_parquet('orders.parquet') o JOIN postgres.public.customers c ON o.customer_id = c.id LIMIT 10;
Then use the same query as a data source — and stream it anywhere.
All in the same workflow.
Note: This is the public home of DBConvert Streams — example configurations, documentation, issue tracking, and release notes. The product itself is proprietary.
Runs anywhere — your laptop, a VPS, or your own infra. No cloud dependency, no vendor lock-in.
Download for Windows, macOS, or Linux — no account required.
Grab dbconvert-streams- .mcpb from Releases and drop it into Claude → Settings → Extensions. It asks for connection strings and folders, and nothing else has to be installed — no DBConvert Streams, no toolchain, no server to run.
postgres://user:password@host:5432/dbname
mysql://user:password@host:3306/dbname s3://bucket/folder?region=us-east-1
Several sources go in the one field, separated by spaces — shop=postgres://… orders=mysql://… — and a single question can join across all of them.
Add folders of Parquet, CSV or JSON files with the folder picker. Every source becomes read-only tools in your chat, and one question can span several of them at once.
One file covers Windows and Linux — the bundle carries a binary for each and picks the right one. macOS is planned for a later release.
Not a Claude user? The same server runs as a container, and every MCP client that can launch one can use it:
docker run -i --rm slotix/stream-mcp "shop=postgres://user:password@host:5432/shop"
Cursor and VS Code can set that up in one click — Add to Cursor · Add to VS Code — VS Code asks for the connection string as you install it; in Cursor you replace the sample one. Folders, S3 keys and the rest: standalone server.
The bundled server is proprietary software, distributed under the DBConvert Streams licence. The MIT licence in this repository covers the examples, docs and assets here, not that binary.
Deploy on any machine with Docker — a local server, a VPS (DigitalOcean, Hetzner, AWS EC2, etc.), or your own infrastructure:
curl -fsSL https://dbconvert.nyc3.digitaloceanspaces.com/downloads/streams/latest/docker-install.sh | sh
DBConvert Streams is a database IDE with built-in migration and real-time CDC.
Browse databases, local files, and S3 storage. Edit data directly. Run federated SQL queries that join tables across different database engines — no intermediate exports needed.
In practice, it comes down to this:
Ask about the database work already open in the desktop app: a table, view, file, SQL console, connection, or migration/CDC stream. AI Chat starts with that live workspace context, so it can inspect schemas and data, explain or repair a failed query, and diagnose stream status without asking you to paste DDL into a separate chat.
Use your own installed agent CLI — Claude Code, Codex, GitHub Copilot CLI, or OpenCode. AI Chat automatically supplies the relevant scoped subset of DBConvert's read-only tools and shows tool activity while it works; it cannot change connections, configuration, streams, or data.
/mcp over HTTP(S)SELECT passes the server-side filter — the AI can look and advise, never writeDBConvert Streams exposes these 27 read-only MCP tools. The names below match the live MCP server.
dbconvert_list_connections — list workspace connectionsdbconvert_get_connection — inspect one connectiondbconvert_list_databases — list databasesdbconvert_list_schemas — list schemasdbconvert_list_tables — list tablesdbconvert_list_views — list viewsdbconvert_describe_table — inspect table columns and keysdbconvert_preview_table — preview table rowsdbconvert_describe_view — inspect a viewdbconvert_preview_view — preview view rowsdbconvert_run_select — run a SELECT querydbconvert_explain_select — explain a SELECT querydbconvert_compare_schemas — compare schemasdbconvert_compare_data_sample — compare data samplesdbconvert_list_streams — list streamsdbconvert_get_stream — inspect a streamdbconvert_get_stream_status — get stream statusdbconvert_get_stream_stats — get stream throughput and statisticsdbconvert_get_stream_recent_errors — inspect recent stream errorsdbconvert_get_stream_recent_logs — inspect recent stream logsdbconvert_list_files — list workspace filesdbconvert_get_file_schema — inspect a file schemadbconvert_preview_file — preview file rowsdbconvert_list_s3_buckets — list S3 bucketsdbconvert_list_s3_objects — list S3 objectsdbconvert_run_federated_select — run a read-only query across sourcesdbconvert_explain_federated_select — explain a federated SELECT queryOnly read-only operations are exposed: the server-side filter permits SELECT, so an AI client cannot alter connections, configuration, streams, or data. For client setup, see the MCP setup guide.
Rapidly move large datasets between databases with automatic schema conversion and validation.
Performance: 23 million rows (4.38 GB) migrated from MySQL to Parquet in 35.7 seconds at 136 MB/s.
Stream INSERT, UPDATE, and DELETE operations from source to target in real-time with minimal latency. Supports CDC to databases, files, and S3 storage.
Browse schemas, view and edit data across multiple database connections with a unified tree navigation:
Join tables across MySQL, PostgreSQL, and file sources (CSV, Parquet) in a single query:
Visualize database relationships with interactive entity-relationship diagrams:
Configure data migration and CDC streams with table selection, custom queries, and transfer settings:
Track data streams with real-time metrics — rows, data size, transfer rates, and per-table progress:
Connect your AI client with one click — it reads the same workspace you see, read-only:
Run it anywhere — no cloud account required, no vendor lock-in.
| Method | Description |
|---|---|
| Desktop | Windows, macOS, Linux — local setup, no account required |
| Self-hosted | Docker / Docker Compose on any machine — local server, VPS, or your own infra |
The Database IDE is free forever. For data migration and CDC streaming, see pricing details.
Most people never touch the API. The UI covers connections, table selection, federated SQL, stream configuration, and monitoring end-to-end. The
curlexamples below are for users who want to script deployments, wire DBConvert Streams into CI/CD, or drive it from another service — not a required workflow.
Connections are managed separately and stream configs reference them by ID. Here are typical workflows via the API.
# Create a MySQL source connection
curl -X POST http://localhost:8020/api/v1/connections \ -H "Content-Type: application/json" \ -d '{ "name": "mysql-source", "type"
Only the beginning is shown; read the rest in the repo