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Infrawise

by Sidd27version 1.0.0i★ –iRuns on your computer
Registry nameio.github.Sidd27/infrawise

Install

Overview

Description from the maker (original English)

Live AWS, database & Kafka infrastructure context for AI coding assistants via MCP.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Databases & datasets

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "infrawise": {
      "command": "npx",
      "args": [
        "-y",
        "infrawise"
      ]
    }
  }
}

Run this in your terminal

claude mcp add infrawise -- npx -y infrawise

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "infrawise": {
      "command": "npx",
      "args": [
        "-y",
        "infrawise"
      ]
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "infrawise": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "infrawise"
      ]
    }
  }
}

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.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Sidd27, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Databases & datasetsi

  • More stars than 0% of the other 954 servers in this category
  • Published to the registry more recently than 74% of the other 954 servers in this category
  • Basic checks equal to or better than 100% of the other 954 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Infrawise safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 17 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

Alternatives

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

by supabase

Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.

Computer or cloud★ 2,993Apache-2.0Updated today
Install

MongoDB MCP Server

by mongodb-js

MongoDB Model Context Protocol Server

Runs on your computer★ 1,157Apache-2.0Updated 2 days ago
Install

README from the maker

Open the README

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.

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.


Why this exists

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:

  • Suggest a .scan() on your Orders table that has 50M rows
  • Recommend adding a GSI on status that you already have
  • Write a SELECT * when you need to keep query cost low
  • Not notice that 5 functions are already hammering the same partition key

With Infrawise, it knows:

  • Your exact table schemas, partition keys, sort keys, and GSIs
  • Which functions query which tables and how
  • Which patterns are already flagged as high severity
  • The exact CREATE INDEX SQL or GSI config for your tables — not generic advice

Installation

Requires Node.js 22 or later (node --version).

npm install -g infrawise

or use without installing:

npx infrawise start --claude

Quick start

cd your-project

infrawise start --claude

That's it. Infrawise will:

  1. Probe your environment and generate infrawise.yaml (first time only — asks which AWS profile to use only if you have several)
  2. Scan your AWS services, databases, and codebase
  3. Write .mcp.json so your editor auto-connects on every future launch
  4. Open Claude Code with all 22 MCP tools ready

Every 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)
  1. [HIGH] Full table scan detected on DynamoDB table "Orders" listAllOrders() scans without any filter — reads every item in the table. Recommendation: Replace Scan with Query using a partition key or add a GSI.
  1. [MEDIUM] PostgreSQL table "users" has no index on column "email" No matching leading-column index was observed for "email"; verify with EXPLAIN. Recommendation: CREATE INDEX CONCURRENTLY idx_users_email ON users(email);
  1. [MEDIUM] DynamoDB table "Sessions" accessed by 6 distinct code paths High access concentration may create hot partition issues at scale.

Demo

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.


Using with AI coding assistants

Claude Code (recommended)
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

Cursor
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.

VS Code
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.

Any editor (no flag)
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.

HTTP transport (alternative)

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" } } }

MCP tools

Every tool is annotated read-only (readOnlyHint: true, openWorldHint: false), so MCP clients that honor annotations can call them without a confirmation prompt.

ToolWhat it provides
get_infra_overviewComplete snapshot — services, counts, high-severity findings, configured flag (data age and per-source status ride the dataHealth block on every response)
get_graph_summaryFull infrastructure graph — all nodes, edges, and findings
get_table_schemaColumn-level schema for named tables/collections — types, PKs, FKs, indexes, DynamoDB keys/billing mode, cost signal (no row data)
analyze_functionIssues 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_gsiExact GSI config for a DynamoDB table + attribute — names the existing index instead when one already covers it
postgres_index_suggestionsExact CREATE INDEX SQL for your actual table
suggest_mongo_indexExact createIndex command for a MongoDB collection + field
mysql_index_suggestionsExact ALTER TABLE ADD INDEX SQL for your MySQL table
get_queue_detailsSQS queues — DLQ status, encryption, FIFO type, visibility timeout, message counts
get_api_routesAPI Gateway APIs (REST, HTTP, WebSocket) — routes, HTTP methods, paths, and Lambda integrations
get_topic_detailsSNS topics — subscription counts, protocols, and filter policies (required message attributes per subscription)
get_secrets_overviewSecrets Manager — names, rotation status, and key names inferred from code (values never included)
get_parameter_overviewSSM Parameter Store — names, types, tiers (values never included)
get_lambda_overviewLambda 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_detailsEventBridge rules — name, state, schedule/event pattern, target functions
get_s3_overviewS3 buckets — versioning, encryption, public access, event notifications
get_log_errorsCloudWatch log group names and retention (metadata only; no message bodies)

| get_stack_outputs | Stack outputs and cross-stack exports parsed from local IaC f

Only the beginning is shown; read the rest in the repo

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