"Project dependency resolution and analysis" matching MCP servers:

A cross-project knowledge graph for MCP that maps features across mobile, backend, and admin codebases, giving AI agents full-stack context.

A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.

A Model Context Protocol (MCP) server that provides tools for interacting with OpenROAD and ORFS (OpenROAD Flow Scripts).

MCP server that analyzes codebases to provide dependency graphs, impact analysis, and file insights across 15+ programming languages, enabling AI assistants to understand project structure and navigate code efficiently.

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

An MCP server that builds a local webpage to view AI plans, reports, and diagrams, so the AI only needs to send a URL pointer instead of long text. It provides three tools (view_plan, view_report, view_diagram) and tracks project changes for diff viewing.

MCP server that provides a live, terminal-native layered dependency map for AI coding assistants, with tools to track and visualize development progress in real time.

Enables AI assistants to interact with Autodesk Civil 3D, allowing them to retrieve project data, create/modify/delete drawing elements, and execute code to automate Civil 3D operations.

An MCP server that turns a rough project idea into a structured spec, running entirely locally inside any MCP-compatible editor.

A research proxy that lets Claude, Cursor, and other MCP clients utilize Gemini's generous free tier for deep codebase analysis without burning your main model's quota!

MCP server for comprehensive code analysis, navigation, and quality assessment across 25+ programming languages.

Analyzes a local codebase and exposes its structure, per-file summaries, dependency graph, and complexity hotspots as tools for MCP clients like Claude.

An MCP server that exposes a Svelte/SvelteKit project's component dependency graph over stdio, enabling AI coding assistants to query component imports, unused components, and route dependencies without an editor.

Local-first MCP server for storing and managing project architecture, modules, data flow, and usage examples with complete privacy.

Enables AI assistants to deeply understand codebases via Knowledge Graphs, supporting fuzzy search, architecture layer queries, call chain tracing, impact analysis, and domain knowledge with multi-project support.

An MCP server that recommends tech stacks for your project. Describe what you're building and get a recommended stack with reasoning, tradeoffs, and what each layer should use.

MCP server for repository mapping, dependency analysis, and architecture diagram generation for JavaScript, TypeScript, and Python projects.

Validates and parses Draw.io XML syntax, enabling analysis and verification of diagram structures, especially for AI-generated content.

Architecture governance MCP server for AI-built codebases, enabling health checks, template management, and project scaffolding with migration support.

Provides AI coding agents with durable architecture memory for repositories by generating structured project maps of responsibilities, relationships, and risks.