DataNexus MCP

security_fetch_dependency_graph

Read-onlyIdempotent

Fetch the full dependency tree for a package version including transitive dependencies. Read-only. No side effects. Idempotent. Hard 8-second timeout — large dependency trees may return partial results. package: Package name. Required. version: Exact version string e.g. 1.2.3. Required. ecosystem: One of PyPI, npm, Maven, Go, Cargo, NuGet, RubyGems. Required. Returns all direct and transitive dependencies with version constraints. Use this to understand full supply chain exposure. Use security_fetch_package_vulnerabilities instead when you only need CVEs for a single package. Verified source: deps.dev (Google). 1-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_fetch_dependency_graph", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema

Name	Required	Description
`package`	Yes	Package name e.g. requests. Required.
`version`	Yes	Package version e.g. 2.28.0. Required.
`ecosystem`	Yes	Package ecosystem: npm, pypi, cargo, go, maven, nuget. Required.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.8/5.0

Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), description adds 'Hard 8-second timeout — large dependency trees may return partial results', '1-hour cache', and 'Read-only. No side effects. Idempotent.'

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?

Description is well-structured and front-loaded with essential action and constraints. It is slightly verbose but every sentence adds value: purpose, parameters, usage guidance, source, cache, fallback. No redundant information.

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 (transitive dependency tree, timeout), description covers purpose, parameters, usage, constraints, source, cache, and fallback. Output schema exists but description also notes return value ('all direct and transitive dependencies with version constraints').

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%, baseline 3. Description adds examples for package ('requests'), version ('2.28.0'), and lists ecosystem values ('One of PyPI, npm, Maven, Go, Cargo, NuGet, RubyGems'), enhancing beyond 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?

Description clearly states 'Fetch the full dependency tree for a package version including transitive dependencies', specifying verb, resource, and scope. It distinguishes from sibling 'security_fetch_package_vulnerabilities' by noting when to use each.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells when to use this tool ('understand full supply chain exposure') and when to use an alternative ('only need CVEs for a single package'). Also mentions source (deps.dev), cache duration, and fallback feedback mechanism.

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

All DataNexus MCP tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0

Disambiguation4/5

Tools are grouped into clear domain prefixes (compliance, domain, frontend_security, etc.) with distinct purposes. Minor overlap exists between frontend_security_detect_typosquatting and security_detect_typosquatting, but descriptions clarify the different scope.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern with snake_case. Irregularities like 'fetch' vs 'audit' and two 'detect_typosquatting' tools exist, but overall naming is predictable within domains.

Tool Count3/5

55 tools is high for a single server given the breadth of domains. Some redundancy (e.g., two typosquatting tools) suggests possible trimming, but the count is justified by the wide coverage.

Completeness4/5

The tool surface covers key operations across domains like compliance, domain, security, legal, and nonprofit. Minor gaps exist, such as limited frontend audit beyond package.json and no general-purpose code scanning.

Resources

Need Help?