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While we may not know when the agentic SOC will arrive, we do know it will need timely and accurate intelligence to make good decisions. To provide that intel, we’re making the GreyNoise MCP Server available today, enabling easy integration of GreyNoise intel by Model Context Protocol (MCP) compatible AI agents.
When an AI agent sees an IP address or CVE in a workflow, it can query GreyNoise in real time and learn:
- Whether that IP is a benign mass scanner (safe to deprioritize),
- A known hostile source actively exploiting CVEs (requires escalation), or
- Completely absent from GreyNoise data (possibly targeted activity worth deeper investigation).
This grounding mitigates the risk of hallucinations and prevents agents from treating every alert equally, enabling more realistic, risk-based automation.
Practical Uses in the SOC
With GreyNoise data inside the reasoning loop, agents can handle several critical tasks more effectively:
- Noise Reduction and Alert Triage
GreyNoise filters out the background chatter of benign scanners and research infrastructure.
- Exploitation Awareness and Vulnerability Prioritization
When GreyNoise tags indicate active exploitation of a CVE, agents can prioritize remediation workflows accordingly.
- Incident Response and Threat Hunting
By pivoting on ASN, domain, and behavioral tags, agents can connect what appear to be isolated alerts to larger coordinated activity and trigger or suggest containment actions (e.g., pushing firewall blocks, updating IPS rules) in a way that minimizes false positives.
- Continuous Monitoring and Risk Awareness
Agents can watch GreyNoise observations in near real time, flagging when exploitation patterns overlap with an organization’s technology stack or internet-facing services.
Why GreyNoise Data Fits Agentic Workflows
SOC teams already use GreyNoise to separate background scanning from true threats. What changes with the MCP Server is that the same logic is now available directly to AI agents.
- Real-Time Intel: Agents query GreyNoise live, ensuring their decisions reflect the latest activity rather than cached or stale data.
- Behavioral Tags: Exploit attempts and reconnaissance behaviors are labeled, allowing agents to reason in higher-level terms than raw IPs and ports.
- Analyst-Equivalent Context: GreyNoise fields—classification, CVE tags, first/last seen, ASN, sensor hit counts—mirror the attributes human analysts check when validating alerts.
This combination makes GreyNoise data especially well-suited to agentic SOC environments, where decisions need to be fast but also defensible.
Lighten the Work of Creating Intel Reports
Let’s say your manager wants an intelligence report, perhaps regarding an external threat, a set of IP addresses, or a vulnerability. For example, I may need to create a report based on a CVE, so I open Claude with the GreyNoise MCP server installed and enter the prompt:
Notice how Claude is making several calls to the GreyNoise MCP server as well as other sources so that it can combine these sources into a report.
Because of the GreyNoise MCP, the report includes details about IP address counts and recent surges in activity. Adding more to the prompt, such as “Tell me about the source geography of the attacks”, causes Claude to generate a much more detailed report. With minimal effort, you can write a prompt that creates just the report that you need. You can even ask for vendor risk reports and threat hunting plans. It’s a great way to reliably use AI to lighten your workload.
Final Thoughts
Agentic SOCs are still an emerging concept, but the risks can be mitigated and the value better realized if AI agents make decisions grounded in trustworthy data. The GreyNoise MCP Server provides a way to embed that grounding directly into agentic workflows.
For security teams, this doesn’t mean replacing analysts—it means giving agents access to the same noise-filtering and exploitation-awareness that practitioners already rely on, so that automation can act responsibly at scale.
Indeed, analysts can make great use of the MCP just by interacting with an LLM application that supports MCP, such as Claude. Conduct research. Look into trends. Generate reports. It’s as easy as it is fun.
Find everything you need to know in the GreyNoise MCP Server docs.
