"Lens" matching MCP servers:

Provides token-efficient code retrieval for coding agents by indexing repositories and enabling ranked snippet search, symbol outlines, and surgical line reads.

Enables deep, AST-based analysis of Next.js projects so MCP clients can understand route hierarchies, client/server boundaries, auth coverage, unused exports, and security issues directly from the codebase.

Deterministic navigation maps over code AND markdown for AI agents: one MCP server, two lenses (tree-sitter TS/JS/Python + markdown). Map a whole project, read one function or one doc-section, ~99% less context. Merges codelens + docslens.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Enables LLM agents to navigate source code structurally via tree-sitter over MCP, offering outline-based reading, AST pattern search, workspace-scale symbol indexing, call graph analysis, and built-in security audit queries.

An MCP server that exposes Ruby on Rails implicit dependencies like callbacks, associations, and concerns to AI coding tools.

An MCP server that provides a flexible lens into directory structures and files, enabling LLM clients to efficiently navigate and understand codebases with minimal noise. It offers secure, gitignore-aware file access with tools like directory listing, file reading, and grep-like search.

Static-analysis MCP server for Django models. 5 read-only tools for AI coding agents.

Enables analyzing and optimizing context window token usage by measuring, compressing, and eliminating waste from MCP tool definitions.

Cross-repository code intelligence server that enables AST-based search for functions, classes, types, and API routes across local JavaScript/TypeScript and PHP repositories.

Enables AI assistants to scan websites, public repositories, and OpenClaw/CLAW skills for security vulnerabilities, including local skill-package analysis before installation, cloud scans, and remediation guidance.

Enables multi-lens code review by running 8 specialized reviewers in parallel, deduplicating findings, and producing a single verdict.

MCP server that builds a dependency graph of your codebase, giving AI agents structural understanding to analyze impact, find context, and make safe modifications across languages and infrastructure.

Enables AI coding assistants to generate bespoke design systems by synthesizing OKLCH color palettes, chamfer highlights and spring physics, teaching layout composition grammar, and returning micro-interaction primitives and component blueprints. Also audits JSX/TSX/HTML through a senior design director's lens to score and critique UI quality.

Provides MCP tools for Claude Code to query a project's codebase via a compact index, reducing token usage and context bloat by enabling symbol lookup, usage tracking, and dead-code detection.

locidx

MCP server for analyzing Perl code with Perl::Critic, enabling code quality checks via both file paths and direct code input.

An MCP server that gives coding agents IDE-like access to JVM classpaths by querying the actual build tool, providing precise source code, signatures, and structure without cache-walking or version guesswork.