smithery Safe content atomic container

watchTowr MCP Server

The watchTowr Platform MCP (Model Compatibility Protocol) Server acts as a real-time integration layer between watchTowr’s world-class External Attack Surface Management and Vulnerability Intelligence technology, and LLM agents, enabling seamless ingestion and understanding of newly discovered threats and exposures. Security teams can now equip AI agents with structured access to timely vulnerability data—empowering use cases from attack surface triage to dynamic reporting and contextual prioritization.

Cognium trust score

30%

Tier

Unverified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-08-24.

Scan details: Circle-IR · 2026-08-24 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: container
Category: ai-ml
Source: Smithery
Author type: human
Last scanned: 2026-08-24
Updated: 2026-08-24

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MCP

Resolve watchTowr MCP Server from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"