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ClaudeWave

MCP server for AWS infrastructure analysis — Lambda, DynamoDB, SQS, PostgreSQL, MongoDB, EventBridge & more. Works with Claude Code, Cursor, and GitHub Copilot.

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Last scanned: 6/11/2026
Install in Claude Code / Claude Desktop
Method: NPX · infrawise
Claude Code CLI
claude mcp add infrawise -- npx -y infrawise
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "infrawise": {
      "command": "npx",
      "args": ["-y", "infrawise"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
Casos de uso

Resumen de MCP Servers

# Infrawise

[![npm version](https://img.shields.io/npm/v/infrawise)](https://www.npmjs.com/package/infrawise)
[![Publish to npm](https://github.com/Sidd27/infrawise/actions/workflows/npm-publish.yml/badge.svg)](https://github.com/Sidd27/infrawise/actions/workflows/npm-publish.yml)
[![CI](https://github.com/Sidd27/infrawise/actions/workflows/ci.yml/badge.svg)](https://github.com/Sidd27/infrawise/actions/workflows/ci.yml)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)
[![infrawise MCP server](https://glama.ai/mcp/servers/Sidd27/infrawise/badges/score.svg)](https://glama.ai/mcp/servers/Sidd27/infrawise)

**[sidd27.github.io/infrawise](https://sidd27.github.io/infrawise/) — Understand your infrastructure, not just your code.**

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

---

## What Infrawise is not

Infrawise is not an AI agent framework, an infrastructure provisioning tool, an observability platform, or a cloud management dashboard.

It is a deterministic infrastructure intelligence layer for AI-assisted development.

---

## Installation

```bash
npm install -g infrawise
```

or use without installing:

```bash
npx infrawise start --claude
```

---

## Quick start

```bash
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 16 MCP tools ready

**Every time after:**

```bash
claude    # no infrawise command needed — editor manages the connection
```

Analysis is cached for 24 hours. When the cache is stale, `infrawise serve --stdio` (spawned automatically by your editor) refreshes it at session start. File changes are detected within the session and the code graph is updated automatically.

```
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.

2. [MEDIUM] PostgreSQL table "users" has no index on column "email"
   Filtering on "email" causes sequential scans.
   Recommendation: CREATE INDEX CONCURRENTLY idx_users_email ON users(email);

3. [MEDIUM] DynamoDB table "Sessions" accessed by 6 distinct code paths
   High access concentration may create hot partition issues at scale.
```

---

## Using with AI coding assistants

### Claude Code (recommended)

```bash
infrawise start --claude
```

Writes `.mcp.json` to your project root 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.

### Cursor

```bash
infrawise start --cursor
```

Writes `.cursor/mcp.json` and opens Cursor. All 16 infrawise tools are available in Cursor's MCP panel.

### Any editor (no flag)

```bash
infrawise start
```

Writes `.mcp.json` 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:

```bash
infrawise serve    # starts server at http://localhost:3000/mcp
```

Add to your editor's MCP config:

```json
{
  "mcpServers": {
    "infrawise": {
      "url": "http://localhost:3000/mcp"
    }
  }
}
```

### MCP tools

| Tool                         | What it provides                                                                                            |
| ---------------------------- | ----------------------------------------------------------------------------------------------------------- |
| `get_infra_overview`         | Complete snapshot — all services, counts, high-severity findings, and a `configured` flag                   |
| `get_graph_summary`          | Full infrastructure graph — all nodes, edges, and findings                                                  |
| `analyze_function`           | Issues in a specific function — scans, missing indexes, N+1, trigger event shapes                           |
| `suggest_gsi`                | Exact GSI config for a DynamoDB table + attribute                                                           |
| `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 and rotation status (values never included)                                         |
| `get_parameter_overview`     | SSM Parameter Store — names, types, tiers (values never included)                                           |
| `get_lambda_overview`        | Lambda functions — runtime, memory, timeout, triggers (SQS/SNS/DynamoDB/Kinesis/MSK/EventBridge/S3), env var key names |
| `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 error patterns and counts (no raw log messages)                                                  |

---

## CLI reference

| Command                       | What it does                                                                       |
| ----------------------------- | --------------------------------------------------------------------------------- |
| `infrawise start`             | **Primary command** — probe env, generate config, analyze, write editor MCP config |
| `infrawise start --claude`    | Same as above, then opens Claude Code                                             |
| `infrawise start --cursor`    | Same as above, then opens Cursor                                                  |
| `infrawise start --interactive` | Run the guided setup wizard instead of auto-discovery                           |
| `infrawise start --rediscover` | Delete `infrawise.yaml` + `.infrawise/`, then re-probe and re-analyze            |
| `infrawise analyze`           | Force a full re-scan — useful after major infrastructure changes                  |
| `infrawise check`             | CI gate — analyze and exit non-zero when findings reach the threshold severity    |
| `infrawise serve`             | Start the MCP server — HTTP by default, or `--stdio` for editor integration       |
| `infrawise doctor`            | Diagnostic escape hatch — validate AWS/DB access, config, and repo scan            |

### `infrawise analyze` options

| Flag                  | Description                                                            |
| --------------------- | ---------------------------------------------------------------------- |
| `-c, --config <path>` | Path to `infrawise.yaml` (default: `infrawise.yaml`)                   |
| `-r, --repo <path>`   | Repository to scan (default: current directory)                        |
| `--no-cache`          | Skip reading/writing the cache                                         |
| `-o, --output <path>` | Save findings as a markdown report, e.g. `report.md`                   |
| `--severity <level>`  | Only show findings at or above this level: `high` \| `medium` \| `low` |

```bash
# Export a shareable findings report
infrawise analyze --output report.md

# Only show high-severity issues
infrawise analyze --severity high

# High-severity issues only, saved to a file
infrawise analyze --severity high --output report.md
```

### `infrawise check` options (CI/CD)

`check` runs a fresh analysis and sets a no
ai-toolsawsclaude-codecursordevtoolsdynamodbiacinfrastructureinfrastructure-analysislambdamcpmcp-servermcp-toolsmodel-context-protocolserverlessterraformtypescript

Lo que la gente pregunta sobre infrawise

¿Qué es Sidd27/infrawise?

+

Sidd27/infrawise es mcp servers para el ecosistema de Claude AI. MCP server for AWS infrastructure analysis — Lambda, DynamoDB, SQS, PostgreSQL, MongoDB, EventBridge & more. Works with Claude Code, Cursor, and GitHub Copilot. Tiene 12 estrellas en GitHub y se actualizó por última vez today.

¿Cómo se instala infrawise?

+

Puedes instalar infrawise clonando el repositorio (https://github.com/Sidd27/infrawise) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar Sidd27/infrawise?

+

Nuestro agente de seguridad ha analizado Sidd27/infrawise y le ha asignado un Trust Score de 87/100 (tier: Trusted). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene Sidd27/infrawise?

+

Sidd27/infrawise es mantenido por Sidd27. La última actividad registrada en GitHub es de today, con 1 issues abiertos.

¿Hay alternativas a infrawise?

+

Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.

Despliega infrawise en tu cloud

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