Dependency Impact Analyzer

Dependency Impact Analyzer MCP Connector for Claude

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Analyzes the security, legal, and structural impact of adding or updating dependencies.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides a suite of tools to mitigate supply-chain security risks in agent-generated code. It allows AI agents to evaluate the full impact chain of any dependency change. Using analyze_dependency_impact, agents can determine risk levels, identify known vulnerabilities, and estimate bundle size increases. The get_dependency_tree_from_manifest tool builds a complete structural view from manifest files, while check_license_compliance ensures all new packages align with project legal policies.

securitydependencysupply-chainvulnerabilitylicense

3 tools expose this connector's capabilities to your AI agent.

analyze_dependency_impact

Determines the security, legal, and structural impact of introducing or updating a specific dependency

check_license_compliance

Validates if a specific package's license is compatible with the project's existing license policy

get_dependency_tree_from_manifest

json or requirements.txt content into a dependency tree. Constructs a structured dependency tree from standard manifest files

See how to talk to your AI agent using Dependency Impact Analyzer.

I want to add 'lodash' version '^4.17.21' to my project. Is it safe?

The dependency 'lodash' at version '^4.17.21' is rated as LOW risk. No known vulnerabilities were found, and it is compatible with your current license policy.

Analyze the impact of updating 'express' to '^4.18.2'.

Updating 'express' to '^4.18.2' results in a MEDIUM risk level due to 3 new transitive dependencies and an estimated bundle size increase of 45KB.

Check if the 'mit' license is compatible with my project policy.

Yes, the 'mit' license is compatible with your project's permitted license policy.

It uses `analyze_dependency_impact` to cross-reference new dependencies against a local vulnerability database, identifying known CVEs before they are installed.

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