About AI Scanner
AI Scanner exposes codebase scans through an MCP server for AI agents. It detects AI SDK and framework usage, inventories models and endpoints, and checks for exposed tokens and hardcoded secrets.
Key features
- 01Scan code for AI SDKs and frameworks
- 02Detect exposed tokens and hardcoded secrets
- 03Run pass/fail secret checks
- 04Inventory models and API endpoints
- 05Include or exclude .env files
Use cases
- 01Check a codebase for exposed API credentials
- 02Run a secret check before committing
- 03Identify AI frameworks and SDKs in a project
- 04Review model references and API endpoints
MCP support
Exposes scan_directory, check_secrets, and ai_inventory tools to MCP clients for scanning a specified directory.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
3Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| ai_only | boolean | No | If true, only scan for AI-specific patterns (skip generic secrets like Stripe, GitHub tokens, etc.) |
| scan_env | boolean | No | If true, include .env files in the scan (skipped by default) |
| directory | string | Yes | Absolute or relative path to the directory to scan |
| include_models | boolean | No | If true, detect model name references (gpt-4, claude, etc.) |
| include_endpoints | boolean | No | If true, detect LLM API endpoint URLs |
Details
From the project README
ai-scanner-mcp
MCP server for ai-scanner - let AI agents scan codebases for LLM usage, AI frameworks, and exposed secrets.
An MCP server that exposes ai-scanner as tools for AI agents. Works with Claude Code, Claude Desktop, Cursor, Windsurf, and any MCP-compatible client.
Tools
| Tool | Description |
|---|---|
scan_directory | Full scan — LLM SDKs, AI frameworks, exposed tokens, and hardcoded secrets with severity levels |
check_secrets | Security check — pass/fail scan for exposed credentials only. Perfect for pre-commit checks |
ai_inventory | AI stack overview — which SDKs, frameworks, models, and API endpoints are used (no secret detection) |
Setup
Claude Code
claude mcp add ai-scanner npx ai-scanner-mcp
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"ai-scanner": {
"command": "npx",
"args": ["ai-scanner-mcp"]
}
}
}
Config file location:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
Cursor
Add to .cursor/mcp.json in your project:
{
"mcpServers": {
"ai-scanner": {
"command": "npx",
"args": ["ai-scanner-mcp"]
}
}
}
Windsurf
Add to ~/.windsurf/mcp.json:
{
"mcpServers": {
"ai-scanner": {
"command": "npx",
"args": ["ai-scanner-mcp"]
}
}
}
Example Usage
Once connected, you can ask your AI agent:
- "Scan this project for any exposed API keys"
- "Check if there are any hardcoded secrets before I commit"
- "What AI SDKs and frameworks does this codebase use?"
- "Run a security scan on ./src and tell me if it's safe to push"
- "Give me an AI inventory of this project"
Tool Details
scan_directory
Full scan with all detection categories. Parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
directory | string | required | Path to scan |
ai_only | boolean | false | Skip generic secrets (Stripe, GitHub, etc.) |
scan_env | boolean | false | Include .env files |
include_endpoints | boolean | true | Detect LLM API endpoint URLs |
include_models | boolean | true | Detect model name references |
check_secrets
Security-focused pass/fail check. Parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
directory | string | required | Path to scan |
ai_only | boolean | false | Only check AI tokens |
scan_env | boolean | false | Include .env files |
ai_inventory
AI stack awareness (no secret detection). Parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
directory | string | required | Path to scan |
Detection Coverage
- AI Tokens (20+) — OpenAI, Anthropic, Google, AWS, HuggingFace, Groq, Replicate, and more
- Generic Secrets (59) — Stripe, Twilio, GitHub, Slack, Discord, database URIs, private keys, JWTs
- LLM SDKs (23) — OpenAI, Anthropic, Google Gemini, LiteLLM, AWS Bedrock, and more
- AI Frameworks (24) — LangChain, LlamaIndex, CrewAI, AutoGen, DSPy, Vercel AI SDK, and more
- 145 total detection patterns
License
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.