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Tenable OT Security MCP Server

Tenable OT Security MCP Server

by aqamahn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get asset intelligence bundle (joined data, not narrative)

get_asset_intelligence

Get a full asset intelligence bundle—core details, open vulnerabilities, recent events, and one-hop peers—so AI can generate a per-asset narrative.

Instructions

Returns one asset's full relational bundle in a single shot: asset core + open vulnerabilities + recent events where the asset is source or destination + 1-hop comms peers. The AI uses this bundle to write a per-asset intelligence narrative if asked. The server does NOT generate the narrative itself.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "asset_id": "<asset_id>"
    },
    "name": "get_asset_intelligence"
  }
}

Input Schema

NameRequiredDescriptionDefault
asset_idYes
max_peersNo
max_vulnsNo
max_eventsNo
recent_event_window_isoNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description discloses the tool's non-narrative behavior and the joined-data nature, which is valuable. However, it does not mention potential performance implications, permission requirements, or side effects. The 'single shot' phrasing hints at efficiency but doesn't elaborate. The disclosure is adequate but not rich.

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

Conciseness5/5

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

The description is two sentences with no redundancy. It front-loads the core function and includes a useful caveat about narrative generation. Every sentence contributes to understanding the tool's purpose and limitations.

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?

The description covers the tool's purpose, output composition, and the context in which the AI uses the result. The output schema exists, so return details are provided by the schema. It does not explain parameter defaults or caps, but for a bundle-returning tool with clear components, the context is largely sufficient.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not explain any parameter meaning beyond naming. Parameters like max_peers, max_vulns, max_events, and recent_event_window_iso are not described, nor how they interact with the returned bundle. The description mentions 'recent events' but not how the window is controlled, leaving ambiguity.

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 description clearly states the tool returns 'one asset's full relational bundle' and enumerates the exact components (asset core, vulnerabilities, events, peers). The title additionally reinforces the distinction from narrative generation. This differentiates it from sibling tools like get_asset or get_asset_vulnerabilities which return individual data views.

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 implies use when a complete relational picture is needed in a single call, and explicitly notes the AI consumes this bundle for narrative writing. It does not name specific alternatives, but the sibling list indicates separate getters exist. While not an explicit 'when-not-to-use', the contextual framing provides clear 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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