MCP Network Sentinel

MCP Network Sentinel is a lightweight monitoring wrapper for MCP servers that records every outbound network interaction made by the server. In environments where an AI assistant relies on third‑party MCP services to fetch sensitive data, the risk of accidental or malicious exfiltration grows. By capturing DNS lookups, TCP/UDP connections, and HTTP/HTTPS requests, the sentinel turns hidden traffic into transparent logs that developers can audit or feed back into compliance pipelines. The resulting JSON file contains a structured timeline of destinations, ports, protocols, and timestamps, enabling rapid investigation of anomalous patterns or data leaks.

The core value lies in its zero‑touch integration: developers simply prepend their MCP server command with the sentinel CLI, and the server runs unchanged inside a monitored sandbox. The sentinel hooks into Node.js's native networking modules (, , , , and ) through module interception, so it does not require any modification to the MCP server code. Logs appear on the console in real time, and an optional flag writes a detailed JSON artifact that can be parsed by CI systems, SIEM tools, or custom dashboards.

Key capabilities include:

• Comprehensive coverage of all outbound connections, including TLS handshakes and DNS queries.
• Real‑time console reporting for quick visibility during development or debugging sessions.
• Persistent JSON logs that capture full request metadata (destination, port, protocol, and timestamps).
• Seamless command‑line integration that requires no changes to the underlying MCP server or its dependencies.
• Lightweight overhead, as the sentinel operates entirely in user space and only intercepts network modules.

Typical use cases span a range of security‑centric scenarios. Security teams can audit MCP servers that access confidential datasets, ensuring no unintended data paths exist. Compliance engineers may generate evidence of network isolation for audit trails. Developers working on AI products that ingest private user data can validate that their MCP server does not reach external endpoints during training or inference. Finally, automated CI pipelines can invoke the sentinel to generate network reports that trigger alerts if unexpected domains or IP ranges appear.

By turning opaque network activity into structured, analyzable logs, MCP Network Sentinel empowers developers to enforce strict data‑handling policies while maintaining the flexibility of third‑party MCP integrations. Its straightforward command‑line interface, combined with comprehensive coverage and minimal performance impact, makes it a practical addition to any AI‑centric development workflow that values transparency and security.