Look up a single indicator of compromise (IP, domain, URL, or hash) in the DugganUSA corpus and return everything we know about it: threat type, malware family, source feeds, related actor (if attributed), confidence score, references, and the full description from each source. Read-only. Use thi...
Part of the Jeevesus — DugganUSA Threat Intelligence MCP server.
Free to start. No card required.
AI agents call enrich-ioc to retrieve information from Jeevesus — DugganUSA Threat Intelligence MCP without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though enrich-ioc only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"enrich-ioc": {}
}
}See the full Jeevesus — DugganUSA Threat Intelligence MCP policy for all 3 tools.
These attack patterns abuse exactly the kind of access enrich-ioc gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Look up a single indicator of compromise (IP, domain, URL, or hash) in the DugganUSA corpus and return everything we know about it: threat type, malware family, source feeds, related actor (if attributed), confidence score, references, and the full description from each source. Read-only. Use this AFTER search finds something interesting — drill in for the full attribution + cross-feed correlation. Or use it directly when triaging a single indicator from your SIEM. Pass the IOC as either indicator or value (both work). Optional type hint: ip / domain / url / hash / auto. Examples: indicator="185.93.3.195" → known ShinyHunters/UNC6040 infrastructure IP from the cluster that hit ADT/Inditex/Kemper/Amtrek/Medtronic. indicator="goldenleafway.lat" → fresh Apothecary/ClearFake .lat rotation domain. indicator="ee28b3137d65d74c0234eea35fa536af" → Volexity-attributed malware MD5 (BrazenBamboo/DEEPDATA campaign). Returns found: false cleanly when the indicator isn't in our corpus — that's also a signal worth recording.. It is categorised as a Read tool in the Jeevesus — DugganUSA Threat Intelligence MCP MCP Server, which means it retrieves data without modifying state.
Register the Jeevesus — DugganUSA Threat Intelligence MCP server in PolicyLayer and add a rule for enrich-ioc: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Jeevesus — DugganUSA Threat Intelligence MCP. Nothing to install.
enrich-ioc is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the enrich-ioc rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for enrich-ioc. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
enrich-ioc is provided by the Jeevesus — DugganUSA Threat Intelligence MCP server (https://analytics.dugganusa.com/api/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 3 Jeevesus — DugganUSA Threat Intelligence MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.