Supabase
MCP server for interacting with the Supabase platform
作者提供的说明(英文原文)
Live AWS, database & Kafka infrastructure context for AI coding assistants via MCP.
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"infrawise": {
"command": "npx",
"args": [
"-y",
"infrawise"
]
}
}
}在终端中运行这条命令
claude mcp add infrawise -- npx -y infrawise粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"infrawise": {
"command": "npx",
"args": [
"-y",
"infrawise"
]
}
}
}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": {
"infrawise": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"infrawise"
]
}
}
}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7日
注册名称已通过 GitHub 账户 Sidd27 验证,该账户拥有此仓库
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(1.0.0)于17天前进入注册中心。
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 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。
Infrawise
Your AI coding assistant finally knows your infra.
Website · Docs · Quick start
Infrawise gives AI coding assistants deterministic infrastructure awareness.
It statically analyzes your codebase, cloud infrastructure, and database schemas, then exposes that context through MCP so tools like Claude Code can understand your actual tables, indexes, query patterns, and service relationships instead of guessing from source files alone.
New software developers don't write wrong code. Claude Code writes wrong code and they ship it. Infrawise is the only thing standing between Claude Code's generated output and a production incident.
AI coding assistants can read your source files but have no deterministic knowledge of your infrastructure. They do not know which GSIs exist, how tables are partitioned, which functions already trigger scans, or where indexes are missing. So they guess.
Infrawise replaces guessing with infrastructure-aware context.
Without Infrawise, an AI assistant might:
.scan() on your Orders table that has 50M rowsstatus that you already haveSELECT * when you need to keep query cost lowWith Infrawise, it knows:
CREATE INDEX SQL or GSI config for your tables — not generic adviceRequires Node.js 22 or later (node --version).
npm install -g infrawise
or use without installing:
npx infrawise start --claude
cd your-project
infrawise start --claude
That's it. Infrawise will:
infrawise.yaml (first time only — asks which AWS profile to use only if you have several).mcp.json so your editor auto-connects on every future launchEvery time after:
claude # no infrawise command needed — editor manages the connection
Analysis is cached for 24 hours. infrawise serve --stdio (spawned automatically by your editor) connects and lists tools without loading the snapshot or running analysis. The first infrastructure tool call loads the cache; if it is missing or expired, that call waits for a fresh analysis. Concurrent calls share that initial analysis. Run infrawise start before opening your editor to prepare the cache and avoid that first-call wait. File watching starts once the snapshot is loaded. HTTP serve still loads its snapshot before listening.
After the first code refresh, the server retains extracted operations and dependency paths, then scans only changed files and their transitive importers. TypeScript ASTs are released as files are processed. Python saves scan only the changed Python files. Added and deleted files update the snapshot, saves are batched for two seconds, and edits made during a refresh are queued. Changing a tsconfig*.json rebuilds the scanner. IaC extraction, graph construction, and analyzers still run across the full snapshot to preserve cross-resource findings; cloud metadata stays cached. No configuration or CLI flags are needed.
Findings (3 total)
Two demos run infrawise against real AWS APIs emulated locally in Docker, at zero cost and with no real AWS account.
demo/floci/ uses Floci, an MIT-licensed emulator that covers every service infrawise supports — including CloudFront, API Gateway v2, RDS, Cognito, Kinesis, ElastiCache, and MSK. No auth token, no sign-up. Start here.demo/localstack/ uses LocalStack community edition, which covers the core services.Both listen on port 4566, so run one at a time.
infrawise start --claude
Writes .mcp.json to your project root (merging with any MCP servers already configured there) and opens Claude Code. Claude Code reads .mcp.json automatically on every launch and manages the infrawise serve --stdio process — no server to start, no ports to configure.
Infrawise is also installable as a Claude Code plugin. It registers the same MCP server and still needs an infrawise.yaml in the project, which infrawise start creates:
/plugin marketplace add Sidd27/infrawise
/plugin install infrawise@infrawise
infrawise start --cursor
Writes .cursor/mcp.json (merging with any existing MCP servers) and opens Cursor. All 22 infrawise tools are available in Cursor's MCP panel.
infrawise start --vscode
Writes .vscode/mcp.json (merging with any existing MCP servers) and opens VS Code. The tools are available to Copilot agent mode via the MCP servers panel.
infrawise start
Writes .mcp.json (merging with any existing MCP servers) and exits. Open whichever editor you prefer — point it at infrawise serve --stdio --config /path/to/infrawise.yaml as an MCP server command.
If your editor or workflow requires an HTTP MCP endpoint instead of stdio:
infrawise serve # starts server at http://localhost:3000/mcp
Add to your editor's MCP config:
{
"mcpServers": { "infrawise": { "url": "http://localhost:3000/mcp" } } }
Every tool is annotated read-only (readOnlyHint: true, openWorldHint: false), so MCP clients that honor annotations can call them without a confirmation prompt.
| Tool | What it provides |
|---|---|
get_infra_overview | Complete snapshot — services, counts, high-severity findings, configured flag (data age and per-source status ride the dataHealth block on every response) |
get_graph_summary | Full infrastructure graph — all nodes, edges, and findings |
get_table_schema | Column-level schema for named tables/collections — types, PKs, FKs, indexes, DynamoDB keys/billing mode, cost signal (no row data) |
analyze_function | Issues in a specific function — scans, missing indexes, N+1, trigger event shapes, missing IAM permissions; returns every same-named file as a separate match, or bind to one with the optional file input; names refused Lambda links and why (unresolvedLambdas) |
suggest_gsi | Exact GSI config for a DynamoDB table + attribute — names the existing index instead when one already covers it |
postgres_index_suggestions | Exact CREATE INDEX SQL for your actual table |
suggest_mongo_index | Exact createIndex command for a MongoDB collection + field |
mysql_index_suggestions | Exact ALTER TABLE ADD INDEX SQL for your MySQL table |
get_queue_details | SQS queues — DLQ status, encryption, FIFO type, visibility timeout, message counts |
get_api_routes | API Gateway APIs (REST, HTTP, WebSocket) — routes, HTTP methods, paths, and Lambda integrations |
get_topic_details | SNS topics — subscription counts, protocols, and filter policies (required message attributes per subscription) |
get_secrets_overview | Secrets Manager — names, rotation status, and key names inferred from code (values never included) |
get_parameter_overview | SSM Parameter Store — names, types, tiers (values never included) |
get_lambda_overview | Lambda functions — runtime, memory, timeout, execution role ARN, triggers (SQS/SNS/DynamoDB/Kinesis/MSK/EventBridge/S3), env var key names, cost signal, why a Lambda could not be linked to its source (unresolvedLink) |
get_eventbridge_details | EventBridge rules — name, state, schedule/event pattern, target functions |
get_s3_overview | S3 buckets — versioning, encryption, public access, event notifications |
get_log_errors | CloudWatch log group names and retention (metadata only; no message bodies) |
| get_stack_outputs | Stack outputs and cross-stack exports parsed from local IaC f
只显示了开头部分;其余内容请在仓库中阅读