Unified MCP server — give your AI agent the ability to secure its own environment.
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# SecurityStack MCP > Give your AI agent the ability to secure its own environment — one MCP config, six tools. > > Audit MCP configs for poisoning, redact secrets/PII before they leave for an LLM, vet untrusted > skills, monitor dependency health, and actively scan your network. All from a single `securitystack` > entry in your agent's MCP config. This is the **client**: the unified MCP server an AI agent (Claude CLI/Desktop, or any MCP-aware agent) installs to call the SecurityStack hosted services. The backend services themselves are hosted — you don't run them. You configure API keys and your agent gets six security tools. ## Why An AI agent has four ways to get compromised. SecurityStack covers all four: ``` 1. What it INSTALLS → poisoned skills / MCP configs → scan_skill + audit_mcp_server_config 2. What it DEPENDS ON → a dependency goes down/rogue → check_dependencies 3. Where it's EXPOSED → open ports, default creds → network_scan (with AI agent loop) 4. What it SENDS OUT → secrets/PII leak into the LLM → scan_secrets ``` Two of these — `audit_mcp_server_config` and `scan_secrets` — run **offline, in-process, with no API key**. They work the moment you install the server. The other four call hosted services (configure their keys to enable them; each is skipped gracefully if unset). ## Install ### 1. Install the server ```bash # From source (clone this repo, then install): git clone https://github.com/<your-org>/securitystack-mcp.git cd securitystack-mcp pip install . ``` *(A `pip install securitystack-mcp` from PyPI will be available once published. Until then, install from source as above.)* ### 2. Add it to your agent For **Claude Desktop / CLI** (`claude_desktop_config.json` or `~/.claude.json`): ```json { "mcpServers": { "securitystack": { "command": "python", "args": ["-m", "stack.unified_mcp_server"], "env": { "ACTIVESCANNER_A…
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