Discover Awesome MCP Servers

Music Media MCP Server

Enables users to generate AI-powered music videos by analyzing visual content to compose matching soundtracks using Google's Lyria model. The server automatically merges audio and media into playable video artifacts that can be rendered inline within MCP-compatible chatbots.

hive-memory

Provides AI coding agents with persistent, graph-connected memory across projects, enabling cross-project context retrieval via synaptic connections and hybrid search.

cathedral-mcp

Persistent memory and identity infrastructure for AI agents. Cross-session wake protocol, drift detection, immutable snapshots, and shared memory spaces — free hosted API

ns-bridge

An MCP server that enables AI assistants to interact with the Netherlands Railways (NS) API for route planning, pricing, and real-time departure information. It provides tools for searching stations, planning trips with connections, and viewing real-time departure boards.

mcp-ssh-tool

SSH automation MCP server that enables Claude and ChatGPT to execute commands, manage files, install packages, and control services on remote servers over SSH — supporting password, key, and agent authentication.

CodeGuard MCP Server

Provides centralized security instructions for AI-assisted code generation by matching context-aware rules to the user's programming language and file patterns. It ensures generated code adheres to security best practices without requiring manual maintenance of instruction files across individual repositories.

Databricks MCP Server

Enables LLM-powered tools to interact with Databricks clusters, jobs, notebooks, SQL warehouses, and Unity Catalog through the Model Completion Protocol. Provides comprehensive access to Databricks REST API functionality including cluster management, job execution, workspace operations, and data catalog operations.

SimpleMCP

A lightweight MCP server that auto-discovers tool kits, enabling tools like SQLite queries and web searches via Tavily API.

Zignet

Enables AI-powered Zig programming assistance through code generation, debugging, and documentation explanation. Uses local LLM models to provide idiomatic Zig code creation and analysis capabilities.

MCP Google Server

A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.

Granola MCP Server

Integrates local Granola.ai meeting intelligence with Claude Desktop to enable searching and analyzing meeting transcripts, notes, and summaries. Users can perform natural language queries to retrieve meeting details, analyze participant patterns, and access full speaker-identified conversations.

Material 3 MCP Server

Provides AI agents with tools to access Material 3 design components, design tokens, icons, and accessibility guidelines across multiple frameworks.

arxiv-latex MCP Server

Servidor MCP para o Claude Desktop que usa o arxiv-to-prompt para buscar e processar fontes LaTeX do arXiv para uma interpretação precisa de expressões matemáticas em artigos científicos.

🚀 Pentest MCP: A Comprehensive Tool for Professional Penetration Testing

NOT for educational purposes: An MCP server for professional penetration testers including nmap, go/dirbuster, nikto, JtR, wordlist building, and more.

OpenFIGI API MCP Server

An MCP server that enables interaction with the OpenFIGI API, allowing users to map securities to financial instrument identifiers through natural language.

Picsha AI MCP Server

MCP server for Picsha AI platform enabling LLMs to search, upload, and manage digital assets through natural language, with secure local proxy and multi-tenant sandbox support.

Timebook

Official MCP server for Timebook (usetimebook.com) — time tracking, invoicing, and bookkeeping for freelancers and solo LLCs. Manage clients and projects, start/stop timers, and log, update, and delete time entries. Stdio via the @squidcode/timebook npm CLI; a hosted OAuth endpoint also exists at https://usetimebook.com/mcp.

CDP MCP

A Chrome DevTools Protocol MCP server that enables direct browser automation with auto-discovery of interactive elements, built-in action verification, and persistent site memory across sessions.

boss-agent-cli

Local MCP server for BOSS Zhipin workflows. Exposes 49 tools for job search, welfare filtering, recruiter messaging, pipeline tracking, and resume optimization for AI agents.

Marketing Master – Landing Page Evaluator

Enables rapid analysis of landing pages for SEO compliance, conversion structure, color contrast accessibility, and performance metrics with automated optimization suggestions and code snippets.

tarn-mcp

CLI-first API testing tool with MCP server. Tests are .tarn.yaml; failures come back as structured JSON for AI agents to branch on. Tools: tarn_run, tarn_validate, tarn_fix_plan, tarn_inspect, tarn_rerun_failed.

shipcheck-mcp

Enables AI agents to run Shipcheck on local JavaScript/TypeScript repositories, scanning for launch risks like exposed env vars, unsigned webhooks, and missing security guardrails.

Controtto

Okay, I understand. I can translate English text to Portuguese. Furthermore, I can analyze Go code and evaluate it based on Domain-Driven Design (DDD) and Clean Architecture principles. I will strive to be strict in my assessment, looking for: * **DDD:** * **Ubiquitous Language:** Is the code using terminology that is clear, consistent, and reflects the domain language understood by domain experts? * **Bounded Contexts:** Are the boundaries of different domain areas clearly defined and enforced? Are there explicit integration points between contexts? * **Entities:** Are entities properly modeled with identity, attributes, and behavior? * **Value Objects:** Are value objects immutable and representing concepts without identity? * **Aggregates:** Are aggregates used to enforce consistency and transactional boundaries? Is the aggregate root clearly defined? * **Repositories:** Are repositories used to abstract data access and persistence concerns? * **Domain Services:** Are domain services used for complex operations that don't naturally belong to an entity or value object? * **Domain Events:** Are domain events used to decouple different parts of the system and react to changes in the domain? * **Clean Architecture:** * **Independence of Frameworks:** Is the core domain logic independent of specific frameworks and libraries? * **Testability:** Is the code easily testable, with clear separation of concerns? * **Independence of UI:** Is the UI completely decoupled from the domain logic? * **Independence of Database:** Is the database implementation a detail that can be easily swapped out? * **Use Cases (Interactors):** Are use cases clearly defined and implemented as interactors that orchestrate the domain logic? * **Entities (Domain Layer):** Is the domain layer pure and free of infrastructure concerns? * **Controllers/Presenters:** Are controllers responsible for handling input and delegating to use cases, and presenters responsible for formatting output for the UI? * **Gateways/Repositories (Interface Adapters):** Are gateways used to abstract external systems and databases? * **Dependency Rule:** Does the code adhere to the dependency rule, with dependencies pointing inwards towards the core domain? **In my analysis, I will consider:** * **Code Structure:** How well the code is organized into layers and packages. * **Naming Conventions:** Whether the naming is clear, consistent, and reflects the domain. * **Coupling and Cohesion:** How tightly coupled the different parts of the system are, and how well each module focuses on a single responsibility. * **Error Handling:** How errors are handled and propagated throughout the system. * **Test Coverage:** The extent to which the code is covered by unit and integration tests. **To get the best results, please provide me with:** * **The Go code you want me to analyze.** * **A brief description of the domain the code is intended to model.** * **Any specific concerns or areas you'd like me to focus on.** I will do my best to provide a thorough and helpful assessment. I will point out potential violations of DDD and Clean Architecture principles, and suggest improvements where possible. Keep in mind that these are principles and guidelines, and the best approach will always depend on the specific context of the project. Let me know when you're ready to provide the code!

wrds-mcp

Provides AI assistants with natural language access to WRDS financial data for credit and equity analysis through 29 specialized tools. It enables users to query bond history, credit ratings, financial metrics, and syndicated loans using simple conversational prompts.

Readwise Reader MCP Server

Enables Claude to interact with the Readwise Reader API, allowing for saving, listing, updating, and deleting documents with complete metadata and content access through natural language.

Kogna MCP Server

Enables interaction with Kogna's multi-agent AI avatar system, allowing users to start conversations, switch between specialized avatars and rooms, and manage conversation history through natural language.

Office-PowerPoint-MCP

Enables AI assistants to programmatically create, manipulate, and analyze Microsoft PowerPoint presentations with advanced formatting and template management.

ms-sentinel-mcp-server

ms-sentinel-mcp-server

tokencost-mcp-server

An MCP (Model Context Protocol) server that provides real-time LLM token pricing data for 60+ AI models across 15 providers.