"DaVinci Resolve" matching MCP servers:

Audits local package folders to generate publish-readiness reports and previews of NPM tarball contents. It helps developers identify and resolve configuration issues like missing types or broken exports before releasing code.

Enables AI coding agents to inspect project dependency versions, resolve version constraints, and audit Python code for deprecated or incompatible APIs using authoritative evidence and local AST analysis.

Exposes a project's Reado code-review annotations (tasks, comments, reading progress, bookmarks) as MCP resources, plus tools for an AI coding agent to resolve review tasks, drive guided pair reviews, and inspect Reado's live browser preview.

Exposes technical debt management to AI coding assistants, enabling them to find, prioritize, and resolve TODO/FIXME/BUG comments across codebases via MCP tools.

Enables coding agents to capture and inspect running projects, resolve real assets from free sources, and check source for design tells, providing an evidence loop for improving websites, games, and motion.

MCP server that helps resolve Robocop static code analysis errors and warnings via LLM, providing tools to get reports and run format.

Enables coding agents to analyze monorepo dependency graphs, detect and resolve circular dependencies, and plan a topological build order via Tarjan SCC and Kahn algorithms. It exposes deterministic, zero-dependency Python AST static analysis over MCP for auditing and refactoring codebases.

A FastMCP-based tool for analyzing logback log files to detect code defects and generate automated fix suggestions. It features intelligent stack trace filtering and token optimization to efficiently identify and resolve application errors.

🐍 🏠 - Code graph for AI agents over MCP: resolves Python and TypeScript calls to fully qualified names and reports the share it could not resolve instead of guessing. Multi-hop impact analysis, authz reachability audit, architectural drift against declared patterns. Local, SQLite. uvx codegraph-brain

Gives coding agents structural understanding of a codebase: it indexes Java and Python repositories to resolve symbols, call sites with confidence tiers, module dependencies, diff impact, and hotspots. It also ships an eval harness that measures whether this context actually helps an agent.

Enables an agent to import real dependency manifests and source excerpts, resolve each cryptographic surface to an algorithm, and assess it against published quantum resource estimates and NIST transition dates. Supports recording migration decisions with shelf-life inputs, replaying the SHA-384 seal chain, and exporting a cited migration plan with a start-by year for every surface.

Fetches GitHub PR comments and intelligently applies fixes directly in workspace files, supporting automatic issue resolution with smart pattern recognition.