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vulnerability-exposure-mcp

vulnerability-exposure-mcp

by MRFrazer25
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Key facts

get_key_facts
Read-onlyIdempotent

Retrieve deterministic investigation facts—ports, reputation, version checks, upgrade/EOL, CISA actions, KEV matches, and a prioritized remediation checklist—to ground vulnerability reports.

Instructions

Facts computed directly from this investigation's tool results, with no model involved, so they are the same on every run: open ports, network, reputation, version check results, upgrade target, end-of-life, CISA's required action, and the CISA KEV split into "confirmed for this target" (NVD version match, or the CVE being analysed) and "related" (product family or vendor). Also a remediation checklist in priority order and the sources used, with when each was queried. Base the report's claims on these. Values contain third-party text.

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": {
      "investigation_id": "<investigation_id>"
    },
    "name": "get_key_facts"
  }
}

Input Schema

NameRequiredDescriptionDefault
investigation_idYesThe investigation_id from investigate_target.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.1
    • addedInput schema / properties / investigation_id / description
      Added value: +"The investigation_id from investigate_target."
  2. First observedv0.1.0

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important behavioral traits: the facts are computed without a model, are stable across runs, include third-party text, split CISA KEV entries into confirmed versus related, and record source query times. These details materially help the agent understand trustworthiness and composition. The annotations already cover read-only/idempotent/non-destructive safety, and the description adds substantial context on top.

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 front-loaded with the core definition and then enumerates outputs, remediation, and sources. It is dense but purposeful, with no obvious filler. Minor length and run-on structure keep it from a 5.

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

Completeness5/5

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

There is no output schema, so the description must explain what the tool returns, and it does so thoroughly: it lists the fact categories, the CISA KEV split, remediation checklist, and sources with query times. It also instructs the agent to base report claims on these facts. For a one-parameter aggregation tool, this is complete enough to call correctly.

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?

There is only one parameter, and schema description coverage is 100%; the schema itself explains that investigation_id comes from investigate_target. The description does not add further parameter detail. With the schema doing the work, baseline 3 is appropriate.

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

Purpose4/5

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

The description states a specific resource and defines it precisely: facts computed directly from the investigation's tool results, deterministically, covering open ports, reputation, version checks, CISA KEV, remediation checklist, and sources. It is clearly an aggregation/readout tool rather than a live lookup. It does not explicitly name sibling alternatives, so it stops just short of full sibling differentiation.

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 a clear directive: 'Base the report's claims on these,' which tells the agent when to use the output. It also implies the tool is used after investigate_target, since the facts come from that investigation's tool results. It does not state when not to use it or contrast it with individual sibling checks, so it lacks explicit exclusions.

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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