Skip to main content
Glama
Sign In
Tenable OT Security MCP Server

Tenable OT Security MCP Server

by aqamahn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Query vulnerability clusters (relational join, not computed)

query_vulnerability_clusters

Identify common CVEs across OT assets, exploit chains, and single-patch leverage points. Query per-asset vulnerabilities or search globally by CVE substring.

Instructions

Returns the per-asset → vulnerabilities join the consuming AI uses to spot common CVEs across multiple assets, exploit chains (KEV + exploit-available + high criticality), or single-patch leverage points (one CVE fixing many). Two modes:

• Pass asset_ids: parallel per-asset traversal of asset.plugins, returning each asset's vulns with the same schema. The AI walks the result to find shared CVEs. • Pass cve_substring only: global plugin search (e.g. 'CVE-2023' for a year-bucket), each plugin coming with its full affectedAssets list joined.

Both args may be combined for a per-asset CVE-filtered view. The server does NOT cluster server-side.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "query_vulnerability_clusters"
  }
}

Input Schema

NameRequiredDescriptionDefault
asset_idsNo
global_limitNo
cve_substringNo
per_asset_limitNo
severity_at_leastNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses a key behavioral trait: the server does NOT cluster server-side, meaning the AI must perform clustering itself. It also explains the two traversal modes. However, it doesn't describe behavior when no arguments are supplied (both optional) or mention that it's a read-only operation, which is a gap.

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 moderately long but well-structured: a lead sentence stating the core purpose, followed by bullet-style mode explanations. It front-loads the most important information and adds necessary caveats without excessive verbosity.

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

Completeness3/5

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

The tool has 5 parameters, no annotations, and an output schema. The description covers the primary use cases and the no-clustering caveat, but it misses parameter semantics for 3 params and doesn't cover the empty-args edge case. Given the tool's complexity, it is above minimal but not fully complete.

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%, so the description must compensate. It thoroughly explains `asset_ids` and `cve_substring`, including their behavior in different modes, but omits `global_limit`, `per_asset_limit`, and `severity_at_least`. Since 3 of 5 parameters lack semantic meaning in both schema and description, the description only partially compensates.

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 a per-asset → vulnerabilities join, with two distinct query modes (asset_ids and cve_substring). This distinguishes it from sibling tools like query_vulnerabilities and get_asset_vulnerabilities by framing it as a relational join for identifying common CVEs, exploit chains, and single-patch leverage points.

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 explicit context for when to use the tool: to spot common CVEs across assets, exploit chains, or single-patch leverage points. It explains the two modes and notes they can be combined. However, it doesn't explicitly say when not to use it or name alternative tools, so it's not a full when/when-not guide.

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

Deploy Server

Other Tools