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Illumio MCP Server

by alexgoller
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Python
Remote

create-ringfence

Create a ringfencing policy for an application by analyzing traffic flows and generating rules that allow only discovered communication partners, reducing segmentation risk without per-port policies.

Instructions

Create a ringfencing policy for an application. This analyzes traffic flows to discover which other apps communicate with this app, then creates a ruleset with:

  1. An intra-scope rule allowing all workloads within the app to communicate on All Services

  2. Extra-scope rules for each remote app+env discovered in traffic, allowing them in on All Services The result is a coarse-grained segmentation that controls which apps can talk to each other, reducing risk without requiring per-port policies. WRITE OPERATION: changes PCE state. In clients that gate tool calls (Claude Desktop, Claude Code), this pauses for the user to approve it -- the call has not failed and must not be retried while waiting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoIf true, analyze traffic and report what would be created without actually creating anything (default: false)
app_nameYesApplication label value (e.g., 'CRM', 'Ordering', 'ELK')
env_nameYesEnvironment label value (e.g., 'Production', 'Staging', 'Development')
selectiveNoIf true, adds a deny rule blocking all inbound traffic to the app. In selective enforcement mode the default action is allow-all, so without this deny rule the ringfence has no teeth. Allow rules for known remote apps are processed before the deny rule (rule order: override_deny > allow > deny > default), so known apps pass through and everything else hits the deny. This gets you to enforcement faster than full enforcement mode.
deny_serviceNoService the selective-mode deny rule covers. Defaults to All Services ('deny everything except the allows above'). Narrow it to deny only specific ports.
ruleset_nameNoCustom name for the ringfence ruleset (default: 'RF-<app_name>-<env_name>')
skip_allowedNoIf true, skip creating rules for remote apps whose traffic is already fully allowed by existing policy. Default is false, meaning rules are created for all observed traffic regardless of policy decision. This makes the ringfence ruleset self-documenting — it shows the complete picture of app connectivity. Set to true for minimal rulesets that only fill policy gaps.
deny_consumerNoControls which consumers the deny rule targets (only used with selective=true). Illumio pushes deny rules to the source workload, so this choice matters: 'any' (default) = IP list Any (0.0.0.0/0) as consumer, deny rule only written to destination workloads inside the scope. Safest, no impact on remote workloads. 'ams' = All Workloads as consumer, deny rule pushed to every managed workload outside the scope. Broader enforcement but wider blast radius. 'ams_and_any' = both All Workloads and Any IP list, maximum coverage for managed and unmanaged sources.any
lookback_daysNoNumber of days to look back for traffic flows (default: 30)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.0

TDQS

A4.3/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden and does so thoroughly. It explicitly flags 'WRITE OPERATION: changes PCE state,' explains that gated clients may pause for user approval, warns that the call should not be retried while waiting, and details rule ordering and how deny rules are pushed to source workloads. This goes well beyond a generic 'update' warning.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but information-dense, with a numbered list breaking down the generated rules and a clearly separated approval caveat. It is front-loaded with the core purpose. Some detail, such as selective-mode rule ordering, is repeated in the schema, so a couple of sentences could theoretically be trimmed, but the structure keeps it navigable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity, nine parameters, and absence of annotations or output schema, the description is very complete: it explains side effects, approval behavior, generated rule types, and coarse-grained intent. The main gap is that it does not describe what the API returns or how to interpret the response after the approval completes, though that is not strictly required for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3 and the description does not need to re-document parameters. It does add high-level context by explaining the overall policy structure and selective-mode rule ordering, but it does not add unique meaning for most individual parameters beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific verb and resource: 'Create a ringfencing policy for an application.' It then distinguishes the tool's behavior from general policy creation by detailing the intra-scope and extra-scope rules it generates. This makes its function clear even alongside siblings like create-ruleset and ringfence-batch.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context: use this when you need a coarse-grained segmentation policy discovered from traffic flows. It explains what the result looks like and even warns about approval pauses in gated clients. However, it does not explicitly contrast itself with alternatives such as ringfence-batch or create-ruleset, so it lacks explicit when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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