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dtrack-mcp

by drewrukin
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Python
Remote

find_duplicate_analyses

Retrieve analyses of duplicate findings across a Dependency-Track project and other projects to reuse prior triage decisions. Filters by analysis state, active projects, and project tags.

Instructions

Find analyses of duplicates of a finding across DT.

Given one finding, returns three parallel lists of duplicates with their current analysis (state + comment history), intended for a triage loop that wants to reuse prior decisions:

  • aliases_in_project — other findings in the same project in the same alias cluster (CVE ↔ GHSA ↔ OSV of the same issue).

  • same_vuln_other_components — same vulnerability uuid on other components/versions in the same project.

  • other_projects — findings in other DT projects that share any id in the target's alias cluster; each entry carries its project uuid/name/version.

Each entry bundles {component, vulnerability, analysis}; entries in other_projects also carry project. Read-only.

Filters (v0.4):

  • states — whitelist of analysis states (e.g. ["NOT_AFFECTED","EXPLOITABLE"]) applied to all three output buckets. target is never filtered.

  • only_analyzed — shorthand for every state except NOT_SET. Ignored when states is non-empty (states wins).

  • active_only (default True) — skip archived/inactive DT projects in other_projects. v0.4 default flip — existing callers that don't pass the flag stop seeing archived hits.

  • project_tag — in other_projects only, keep projects carrying this tag (case-insensitive name equality).

  • compact — strip bulky fields (description, CVSS vectors, analysis details, long comment bodies truncated to 200 chars). See SPEC §13.4.1 for the exact field list.

Args: project_uuid: DT project UUID of the target finding. component_uuid: DT component UUID of the target finding. vulnerability_uuid: DT vulnerability UUID of the target finding. states: Whitelist of analysis state strings, e.g. ["NOT_AFFECTED","EXPLOITABLE"]. only_analyzed: If true, keep only entries with a non-NOT_SET analysis. Ignored when states is non-empty. active_only: If true (default), skip archived projects in other_projects. project_tag: Optional DT tag name; restricts other_projects to projects carrying this tag (case-insensitive). compact: If true, strip bulky fields from the payload.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_uuidYes
component_uuidYes
vulnerability_uuidYes
statesNo
only_analyzedNo
active_onlyNo
project_tagNo
compactNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.5/5.0
Behavior4/5

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

The description explicitly states 'Read-only,' which is a key behavioral trait. It also details the output structure and filters. However, no annotations exist, and the description does not disclose authorization requirements or rate limits, leaving some gaps.

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 well-structured with clear sections and bullet points, front-loading the core purpose. While every sentence is informative, the length could be slightly reduced without losing clarity.

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?

Given the tool's complexity (8 parameters, no annotations, rich output), the description is remarkably complete. It covers the three output lists, parameter details, and edge cases (e.g., active_only default flip). The output schema exists but the description adds important context.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by explaining each parameter's purpose, default values, interaction rules (e.g., states wins over only_analyzed), and behavioral impacts (e.g., active_only default flip). This adds substantial meaning beyond the schema.

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 finds duplicate analyses of a given finding across DT, and explains the three parallel lists (aliases_in_project, same_vuln_other_components, other_projects) with specific definitions. This is specific and distinguishes the tool from other search/filter tools.

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 frames the tool as 'intended for a triage loop that wants to reuse prior decisions,' providing clear context. However, it does not explicitly contrast with sibling tools like carry_over_triage or diff_findings, or state when not to use it.

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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