"Lens" matching MCP servers:

MCP server for visual feedback, video direction, and QA assertions on web pages, enabling AI agents to read, reply, and resolve annotations in real time.

A reference implementation of the mcp-lens pattern for progressive disclosure in MCP servers. It exposes three stable meta-tools to search, inspect, and execute capabilities, keeping tool-definition costs constant as the catalog grows.

Lens-MCP is a read-only Postgres MCP server that lets AI agents inspect and query approved database data safely.

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.

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.

MCP server that scans workspace roots to build a registry of version-controlled projects, exposing tools for searching, listing, and inspecting projects to help AI coding agents navigate multi-repo workspaces efficiently.

Acts as a proxy/router for multiple downstream MCP servers, exposing only meta-tools to the host to reduce token usage, enabling efficient search and invocation of tools from a fleet of servers.

MCP server that enables inspecting, controlling, and safely automating live opencode TUI sessions.

Full featured MCP Server for MongoDB database analysis.

A 100% local development monitoring tool that captures browser console logs, network requests, and backend server output for analysis by AI assistants via MCP. It enables LLMs to debug applications by providing structured, real-time access to full-stack log data and persistent local storage.

Provides token-efficient, read-only Figma inspection for coding agents via MCP, enabling extraction of design specs, screenshots, and assets from bounded node subtrees with local caching.

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

MCP server to connect MySQL DB for read-only queries. It offers accurate query execution.

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.

Securely connect AI assistants to PostgreSQL databases with read-only access, schema discovery, querying, and performance analysis tools.

Lets agents and CLI users inspect the shape of large JSON and JSONL files and extract exactly the values they need using jq-like expressions, returning compact bounded results instead of flooding context.

Provides AI agents with deep visibility into a running web page's UI by capturing DOM, styles, and screenshots through a lightweight bookmarklet. It facilitates design-to-code comparisons, accessibility audits, and automated CSS debugging directly within an IDE.

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