VulnTracker MCP

track

Idempotent

Start watching something in VulnTracker for the API key's team: a product (default; slug or id from search_products / check_dependencies matched_slug), a vendor, a single CVE, or a keyword. New CVEs matching the tracking reach the team's board and its notification channels. Plan tracking limits apply; the error says so when the limit is reached. Use when the user asks to 'track', 'watch' or 'follow' the dependencies of a repository; prefer tracking products over individual CVEs.

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": {
      "target": "<target>"
    },
    "name": "track"
  }
}

Input Schema

Name	Required	Description
`type`	No	product (default), vendor, cve or keyword
`notes`	No	Optional note, e.g. 'used by repo X'
`target`	Yes	Product/vendor slug or id, CVE id, or keyword text
`min_severity`	No	Minimum severity to notify for: 0 all, 1 low, 2 medium, 3 high, 4 critical. Omit for the team default
`exploited_only`	No	Only notify when the CVE has known exploitation
`version_filter`	No	Optional version filter for a product, e.g. '>=3.0'

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations cover the safety profile (not readOnly, idempotent, non-destructive), and the description adds behavior beyond them: matched CVEs are pushed to the team's board and notification channels, and plan tracking limits produce a specific error. The downstream side effect and the limit failure mode are exactly the kind of context annotations cannot carry.

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?

Three sentences, front-loaded with purpose before the usage trigger and the preference rule. The first sentence is dense with nested parentheticals, which slightly slows scanning, but no sentence is disposable.

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?

For a six-parameter write tool with no output schema, the definition covers purpose, target sourcing, side effects, and a failure mode. The only gap is what a duplicate tracking call returns, though idempotentHint=true already signals that it is safe to repeat.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds real value by naming 'product' as the default type and telling the agent where valid target values come from (slug or id from search_products / check_dependencies matched_slug). It also repeats the target variants in prose, which reinforces the enum-less 'type' field.

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 opens with a specific verb+resource ('Start watching something in VulnTracker for the API key's team') and enumerates the four trackable target kinds, including which one is the default. It names sibling tools (search_products, check_dependencies) as the source for a product slug, so an agent can distinguish this from a search or a dependency check without opening another schema.

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?

It supplies explicit trigger vocabulary ('track', 'watch', 'follow') and an intra-tool preference rule ('prefer tracking products over individual CVEs'). It does not state the inverse case (use untrack to remove a tracking) or when to pick a keyword over a vendor, so there is clear context but no full when-not 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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