SecureCode MCP

Standalone MCP (Model Context Protocol) server for SecureCode AI. Provides security scanning tools to AI coding assistants — Cursor, Claude Code, Codex, Windsurf, and other compatible MCP clients — without requiring the VS Code extension.

Install

npm install -g @securecode-ai/mcp

Or use directly with npx (no install needed):

npx @securecode-ai/mcp scan src/app.ts

Related MCP server: Secure Code Review MCP Server

Quick Start

securecode-mcp login              # Authenticate (email + OTP)
securecode-mcp doctor             # Verify your setup works
securecode-mcp scan src/app.ts    # Scan a file from the CLI
securecode-mcp serve              # Start the MCP server (for AI clients)

CLI Commands

securecode-mcp serve [--workspace <path>]         Start the MCP stdio server
securecode-mcp login [--api-url <url>]             Authenticate via email + OTP
securecode-mcp status                              Show current auth status
securecode-mcp logout                              Remove stored credentials
securecode-mcp scan <filePath> [--json]            Scan a single file
  [--depth <fast|deep|agent>] [--workspace <path>]
securecode-mcp doctor                              Verify setup (credentials, API, scan)
securecode-mcp --help                              Show help

Scan from CLI

# Agent scan (deep, AI-powered)
securecode-mcp scan src/app/api/users/route.ts

# Fast scan (no AI, free, <5s)
securecode-mcp scan src/lib/auth.ts --depth fast

# JSON output for CI
securecode-mcp scan src/app.ts --json

# Exit codes: 0 = no findings, 1 = findings found, 2 = error

CI/CD Example

# GitHub Action
- name: SecureCode scan
  run: |
    npm install -g @securecode-ai/mcp
    securecode-mcp login  # or set SECURECODE_API_TOKEN
    securecode-mcp scan src/ --json > scan-results.json
    # Exit 1 if findings found

MCP client configuration

Cursor / Windsurf

{
  "mcpServers": {
    "securecode": {
      "command": "npx",
      "args": ["-y", "@securecode-ai/mcp@latest", "serve", "--workspace", "/path/to/your/project"],
      "env": {
        "SECURECODE_API_TOKEN": "your-api-token-here"
      }
    }
  }
}

Or if installed globally:

{
  "mcpServers": {
    "securecode": {
      "command": "securecode-mcp",
      "args": ["serve", "--workspace", "/path/to/your/project"]
    }
  }
}

Claude Code

claude mcp add securecode -s user -- securecode-mcp serve --workspace /path/to/your/project

Tools (17)

Scanning

Project Analysis

Fixes & Testing

Agent Memory (FP Learning)

Finding Review

How Agent Memory Works

When the agent reports a false positive, dismiss it with record-false-positive. The agent stores the pattern in .securecode/agent-memory.json and will not report similar patterns in future scans of that workspace.

Scan 1: Agent reports csp_bypass → You dismiss as "intentional design"
Scan 2: Agent sees the FP memory → skips similar patterns → fewer false positives

Memory is per-workspace, user-owned, and deletable. No cross-tenant leakage.

Agent Scan Architecture

The agent scan (securecode.agent-scan) is an AI security investigator that:

1. Maps the project architecture (architecture scout with trust boundaries, security controls, risks)

2. Reads the target file and related files across the codebase

3. Traces data flows (taint tracking, cross-file flow with structured source→sink→hop chains)

4. Checks guards, endpoint policies, and configuration

5. Verifies threat model applicability and capability reachability

6. Self-critiques before reporting (selfCritique field)

7. Gets reviewed by an independent critique LLM

8. Proves findings in a sandbox (PROVEN/UNPROVEN)

9. Generates fixes for proven findings

Agent tools (20+): read_file, search_code, trace_flow, trace_flow_cross_file, check_guard, check_policy, get_endpoints, list_imports, list_files, call_graph, git_blame, git_history, git_diff, check_dependencies, read_config, find_definition, find_references, find_tests, run_tests, finish.

The deterministic control plane enforces proof quality:

• Every finding requires source, reachability, control, threat-model, and impact evidence

• Unproven concerns become investigation notes, not findings

• Architecture risks expand across related files (callers, implementations, sinks)

• The finish gate rejects finish while proof requirements remain unsatisfied

Languages: JavaScript, TypeScript, Python (partial).

Environment Variables

Security

• Credentials stored in OS keychain (Windows Credential Manager, macOS Keychain, Linux Secret Service) with file fallback (~/.securecode/credentials.json, mode 0600).

• File reads are confined to the --workspace root.

• Fixes are returned for review and never auto-applied.

• Agent memory is per-workspace (.securecode/agent-memory.json), never sent to the API.

• No telemetry.

Development

npm install
npm run build
npm test

License

MIT