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

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

npm install -g infrawise

or use without installing:

npx infrawise init

Quick start

1. Initialize in your repo

cd your-project
infrawise init

Detects your AWS profile and region, asks a few questions, writes infrawise.yaml. That's the only file it creates in your project.

2. Validate everything is connected

infrawise doctor

3. Run analysis

infrawise analyze

Or skip this step — infrawise dev auto-runs analysis if no cache exists.

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

Step 1: Start the MCP server

infrawise dev

  ✔ Config loaded          infrawise.yaml
  ✔ Cached analysis loaded 42 nodes · 18 edges · 7 finding(s)
  ✔ Server running

  ┌────────────────────────────────────────────────────┐
  │ MCP Server                                        │
  ├────────────────────────────────────────────────────┤
  │ POST http://localhost:3000/mcp                    │
  │ GET  http://localhost:3000/health                 │
  ├────────────────────────────────────────────────────┤
  │ Tools (13 active)                                 │
  │ get_infra_overview · get_graph_summary            │
  │ ...                                               │
  └────────────────────────────

... [View full README on GitHub](https://github.com/sidd27/infrawise#readme)