Browse the catalog

This MCP server provides asynchronous video generation capabilities using Amazon Nova Reel 1.1 through AWS Bedrock, enabling AI agents to create videos from text prompts with comprehensive parameter control including duration, frame rate, and dimensions. Built using Python with FastMCP and boto3, it offers four core tools: start_async_invoke for initiating video generation jobs with validation and S3 storage, list_async_invokes and get_async_invoke for monitoring job status and retrieving completed videos, and get_prompting_guide providing detailed best practices based on AWS documentation for effective video prompts including camera control, lighting, and narrative structure. The implementation supports three transport methods (stdio, SSE, HTTP streaming), features persistent job tracking with JSON storage, Docker containerization with multi-architecture support, and includes detailed prompting guidelines covering shot types, camera movements, lighting conditions, and example prompts for different video categories, making it valuable for automated video content creation, marketing material generation, and building AI assistants that need video production capabilities without manual AWS console access.

Provides read-only access to Google Search Console data, allowing AI assistants to query site performance metrics like keywords, clicks, and rankings using natural language. It supports listing verified properties, querying search analytics with dimension filters, and retrieving sitemap information.

MCP server for AFKBot PTO management — file time-off requests from any MCP client

MCP server for the AKKA Finance DEX aggregator — swap quotes, routes, and execution across EVM chains.

Enables searching and querying City of Yakima GIS open geospatial datasets, such as parcels and zoning, through ArcGIS Feature Services.

Minimal MCP server exposing the Connectif HTTP API to MCP clients over stdio, enabling operations like contacts, purchases, products, exports, imports, workflows, and more.

Gives LLMs live, accurate access to Team Fortress Wiki content, enabling search, page retrieval, structured weapon stats, patch notes, and other TF2-specific information.

This MCP server implementation provides Ethereum wallet management and blockchain interaction capabilities. Developed by zhangzhongnan928, it offers tools for creating and importing wallets, checking balances, sending transactions, and deploying/interacting with smart contracts via Infura. The server is designed for use cases requiring AI assistants to manage Ethereum wallets, execute transactions, or interact with EVM-compatible blockchains through a secure, locally-run interface.

This PostgreSQL MCP server implementation by Logesh provides AI assistants with direct database query execution capabilities for PostgreSQL databases. Built with Python using psycopg2, loguru, and FastMCP, it offers a single query_data tool that handles both SELECT queries (returning fetched rows with metadata) and write operations (INSERT, UPDATE, DELETE) with automatic transaction management. The implementation supports both stdio and HTTP transport modes, includes comprehensive error handling and logging, and is preconfigured to connect to a 'litellm' database with standard PostgreSQL credentials, making it suitable for AI-assisted database administration, data analysis workflows, and educational purposes where conversational database interaction is needed.

Provides security verification tools for AI agent skills through the Skvil network. Supports skill verification by SHA-256 hash with reputation scores and risk levels, community scan submission, on-chain certification checking (V1 through Gold levels via Solana SPL Memo transactions), and suspicious skill reporting. Includes automated Crucible behavioral analysis with static analysis across 32+ pattern categories and AI-driven triage.

This MCP server, developed by Apify, provides a web browsing interface for large language models and RAG pipelines. Built in JavaScript, it integrates with the RAG Web Browser Actor on the Apify platform to enable AI assistants to perform web searches, scrape content from top results, and fetch individual URLs. The implementation stands out by returning cleaned web content as Markdown and offering flexible search result limits. By connecting AI models with real-time web data, this server allows AI systems to access up-to-date information, analyze online content, and provide web-informed responses. It is particularly useful for scenarios like research tasks, content summarization, and building AI assistants that can leverage current web information to enhance their knowledge and capabilities.

A TypeScript-based MCP server that provides project-specific knowledge graph memory for LLM agents to store and retrieve entities, relations, and observations. It features disk-persistent storage and supports cross-project knowledge sharing to enhance agent long-term memory.

Document editing, AI writing, saved documents, DOCX downloads, PDF, STT, TTS and watermarking

Enables voice input for AI coding assistants by recording audio, transcribing it locally with Whisper, and optionally typing the text at the cursor position. Supports multiple languages and works with MCP-compatible tools like OpenCode, Claude Code, and Cursor.

A read-only MCP server that exposes Zephyr Scale Cloud test data to review a Jira story's test coverage, answering whether tests are adequate and passing.

Enables travel package management, booking, and itinerary planning through MCP-compliant endpoints with 26 tools for searching, comparing, and booking travel packages.

14 web scrapers as MCP tools for AI agents: Reddit, Amazon, Google Maps, Yelp, YouTube, Indeed & more.

Provides real-time Venezuelan economic data, including official and parallel exchange rates, inflation statistics, and basic goods basket prices. It enables AI assistants to query historical economic trends and current market indicators via natural language.

Connects MCP-powered AI agents to the decentralized Agent Network Protocol (ANP) for DID-based identity, agent discovery, and secure agent-to-agent communication.

MCP server for Legalize.dev, enabling AI to query and understand legal frameworks across countries via a structured legislation API.