Supabase
MCP server for interacting with the Supabase platform
作者提供的说明(英文原文)
Read-only SQL across your PostgreSQL, MySQL, S3 buckets and local data files, in one query.
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 …”。
链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
claude mcp add streams -- npx -y @dbconvert/stream-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"streams": {
"command": "npx",
"args": [
"-y",
"@dbconvert/stream-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": {
"streams": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@dbconvert/stream-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
注册名称已通过域名 dbconvert.com 验证(注册中心会核实域名所有权)
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(2.7.3)于2个月前进入注册中心。
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 MCPB, Docker, Node.js。
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。
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"
只显示了开头部分;其余内容请在仓库中阅读