EUVDB MCP Server

EUVDB MCP Server – A Bridge Between AI Assistants and ENISA’s Public Vulnerability Feed

The EUVDB MCP Server solves a common pain point for security engineers and developers: accessing up‑to‑date vulnerability data from the ENISA EUVDB Public Vulnerability API in a way that is natively consumable by Model Context Protocol (MCP)–compatible assistants such as Claude Desktop or the VSCode extension. Rather than manually querying a REST endpoint and parsing JSON, this server exposes a set of high‑level tools that encapsulate the API’s logic and return data in the structured format expected by MCP clients. This integration allows AI assistants to act as “vulnerability search engines,” automatically populating code reviews, threat models, or incident response playbooks with the latest risk information.

At its core, the server is a lightweight Python application that listens for MCP requests and forwards them to ENISA’s API via HTTP. Each tool corresponds to a common use case: retrieving the newest vulnerabilities, filtering by severity or exploitation status, or looking up a specific CVE or ENISA ID. The server handles pagination and rate limits internally, returning concise lists of up to eight items per call—a design choice that keeps responses snappy for conversational AI interactions. Advanced queries are also supported, allowing clients to specify complex filters such as CVSS score thresholds, EPSS values, or product names, thereby giving developers granular control over the data they pull into their workflows.

For developers building AI‑augmented security tooling, this server offers several key advantages. First, it abstracts away the intricacies of ENISA’s API—authentication, endpoint URLs, and data mapping are hidden behind a clean MCP interface. Second, because the server adheres to MCP standards, it can be plugged into any MCP‑aware assistant without modification; the same tool set works in Claude Desktop, VSCode, or other future clients. Third, the server’s Docker image makes deployment trivial in CI/CD pipelines or container‑native environments, ensuring that teams can expose the same vulnerability data to all members regardless of local setup.

Typical real‑world scenarios include: a DevSecOps pipeline that automatically queries for critical vulnerabilities before a merge, a security analyst using VSCode to fetch the latest advisories while drafting an incident response plan, or a compliance officer employing Claude Desktop to generate audit reports that reference current CVE data. In each case, the server reduces manual effort and eliminates the risk of stale or incomplete information.

In summary, the EUVDB MCP Server turns ENISA’s rich vulnerability repository into a first‑class AI assistant capability. By providing ready‑made, conversationally friendly tools that hide API complexity and fit seamlessly into existing MCP workflows, it empowers developers and security professionals to keep their codebases and operations aligned with the latest threat landscape.