Threatnews MCP Server

The Threatnews MCP server is designed to bridge the gap between AI assistants and real‑time cyber‑threat intelligence feeds. In many security operations, analysts rely on disparate data sources—vendor alerts, open‑source feeds, and internal telemetry—to build situational awareness. This server consolidates that complexity by exposing a single, well‑defined tool () that accepts a date range and returns structured threat data. By doing so, it eliminates the need for developers to write custom scrapers or parsers for each feed, allowing AI assistants to retrieve up‑to‑date threat information with a single command.

At its core, the server runs a lightweight Python script () that queries external APIs using an API key supplied via the environment. The tool accepts arguments such as , , , and their end‑date counterparts, enabling precise temporal filtering. The output is a JSON payload containing threat titles, descriptions, severity levels, and source URLs. This format is immediately consumable by downstream processes—whether the AI assistant needs to summarize an incident, trigger a ticketing system, or feed a visual dashboard. The server’s integration with MCP’s prompt and resource mechanisms means developers can embed the tool in custom prompts, ensuring that the assistant can ask for “threats between March 1 and March 10, 2024” without any additional plumbing.

Key capabilities include:

• Temporal filtering: Retrieve threats for any arbitrary date range, making historical analysis and trend monitoring straightforward.
• Environment‑based configuration: API keys and other secrets are injected via , keeping credentials out of the codebase.
• Extensibility: The same MCP framework can be paired with a Neo4j knowledge‑graph server (as shown in the README), enabling graph‑based queries over the collected threat data.
• Simplicity: The server is launched with a single command, making it trivial to spin up in development or CI environments.

Typical use cases span from automated threat reporting—where an AI assistant pulls the latest alerts and compiles a daily digest—to incident response automation, where real‑time feeds trigger playbooks in security orchestration platforms. Security teams can also leverage the server to populate a knowledge graph, allowing advanced analytics such as attack‑path inference or correlation across multiple threat feeds.

By integrating Threatnews into an AI workflow, developers gain a reliable, consistent source of threat intelligence that can be queried on demand. The server’s design aligns with MCP’s philosophy of modular, tool‑centric interactions, ensuring that AI assistants can focus on higher‑level reasoning while offloading data retrieval to a dedicated, well‑tested component.