"Understanding the concept of dependency" matching MCP servers:

A minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

Read-only npm dependency diagnostics: inventory, audit and health checks from package-lock.json, no account needed.

Checks npm and PyPI packages for outdated versions, deprecation status, and breaking changes with cited sources, enabling AI agents to verify dependency freshness.

MCP server that evaluates compatibility between exact versions of packages and runtimes using official evidence, returning structured verdicts (supported/unsupported/unknown) with sources and limitations.

An MCP server that uses Google's Gemini API to analyze videos and convert them to text descriptions that Claude Code can understand and act upon.

Enables AI clients to search curated, cited knowledge bases built from founders', CEOs', and investors' public talks, essays, and posts, returning passages with source links and dates. It also exposes available source collections via MCP tools so users can ask how those individuals might approach business, product, or growth questions.

Enables interacting with the GTA7 Lab city bank through MCP tools, including balance checks, transaction searches, PIX transfers, bill payments, card issuance, loan simulation and requests, and investments.

Records a sale of a vehicle, equipment or stock and produces a printable bill of sale with signature lines. Drafts can be edited and finalized into a frozen signing copy rendered as Markdown or self-contained HTML for print-to-PDF.

Enables building client statements of account from existing invoices, credit notes, and deposits, with aged outstanding balances, PDF/plain-text output, and drafted payment chasers at friendly, firm, or final levels.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.

Free remote MCP for Core Web Vitals metrics by CMS, CDN, and framework (Chrome field data + multi-site crawl). No auth. Endpoint: https://www.corewebvitals.io/api/state-of-cwv/mcp

Automatically extracts technical concepts from AI coding conversations, organizes them into a searchable knowledge base with hierarchy and categories, and links them to specific locations in your codebase.

Provides access to thousands of interactive self-awareness scenarios, behavioral archetypes, and breakthrough exercises from the Levels of Self development game. It enables AI assistants to guide users through pattern recognition and developmental coaching across seven levels of self-awareness.

Enables AI agents to search and modify a personal knowledge base through OAuth-secured MCP tools, covering Obsidian vaults and Google Drive mirrors with semantic search, note read/write operations, audit logging, and eval-gated local classification.

Enables AI agents to search The Met's open-access collection by keyword with filters for images, on-view status, medium, and year range, and to fetch rich object details such as artist bio, dimensions, department, and gallery number. Also lists the museum's curatorial departments so searches can be scoped, all without an API key.

Enables AI agents to search and retrieve UK company data, including company details by Companies House number, group ownership structures, website associations, and Real-Time Industrial Classification definitions.

A scientific reasoning framework that leverages graph structures and the Model Context Protocol (MCP) to process complex scientific queries through an Advanced Scientific Reasoning Graph-of-Thoughts (ASR-GoT) approach.

Transforms prompts into Chain of Draft (CoD) or Chain of Thought (CoT) format to enhance LLM reasoning quality while reducing token usage by up to 92.4%, supporting multiple LLM providers including Claude, GPT, Ollama, and local models.