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A local, read-only MCP server that lets AI agents inspect and analyze photo libraries by scanning files, aggregating EXIF stats, finding duplicates, scoring blur, and generating cull reports without uploading any data.

Kula's official MCP Server

Enables querying community-run, keyless football/soccer match data from OpenLigaDB through natural language or direct tool calls.

linkedin-humblebrag MCP — wraps StupidAPIs (keyless — no credential needed)

Enables AI assistants to search and apply for jobs on Handshake, track applications, and research employers using your browser session.

Integrates Everything file search with Claude Desktop, enabling instant Windows filesystem search via natural language queries.

A Model Context Protocol server that provides real-time weather data to AI clients through Server-Sent Events, enabling them to fetch current weather conditions, multi-day forecasts, and location-based weather information.

Enables interaction with ERPNext instances via its REST API to manage documents, inventory, and reports. It supports full CRUD operations, submittable document workflows, and schema inspection through natural language.

Provides comprehensive access to Metabase's business intelligence platform, enabling AI assistants to interact with databases, dashboards, cards (saved questions), collections, users, and permissions through a complete set of CRUD operations. Built with robust error handling, extensive test coverage, and type-safe schemas using Zod validation, this implementation supports both MBQL and native SQL query execution, data export in multiple formats, and full administrative capabilities including user management and permission configuration.

Enables MCP-compatible clients to interact with a CiviCRM installation through its APIv4, providing tools for contact management, events, contributions, and more with configurable safety features.

Provides read-only access to Trading 212 accounts, enabling AI assistants to retrieve portfolio positions, account summaries, instrument data, and transaction history.

Enables AI agents to search and list Microsoft Edge browser favorites by keyword, folder, or list all folders.

Enables high-quality 3D-style cartoon image generation using Google Gemini AI alongside secure file system operations like reading, writing, and managing directories. It provides a dual-purpose toolkit for creative asset generation and local file management via the Model Context Protocol.

An MCP server for the IndexNow protocol that lets AI agents instantly submit URLs to Bing, Yandex, Seznam and Naver for fast indexing.

This server enables interaction with PostgreSQL databases through the Model Context Protocol, optimized for the AWS Bedrock AgentCore Runtime. It provides tools for executing read-only queries, exploring database schemas, and monitoring table statistics or slow queries.

Bridges MCP clients to the TubeAlfred YouTube API, enabling tools for video details, transcripts, comments, search, and channel info.

Connects to a local ChatLab instance to query imported chat sessions and message history. Provides session listing, message retrieval with keyword and date filtering, member management, statistical overviews, and SQL-based aggregation queries for analyzing conversation patterns across platforms.

Enables a weekly review of Todoist tasks by listing overdue tasks with key signals (days overdue, priority, times postponed) and letting Claude propose fixes per task, which you approve or veto in chat before any changes are applied.

A local MCP server that connects Claude Desktop to your HelpPilot tenant on pilot.helpvisor.gr, forwarding tool calls and prompts over HTTPS.

This MCP server for memory management, developed by an unnamed creator, provides a simple interface for AI assistants to store and retrieve contextual information in a text file. It integrates with the Model Context Protocol to offer operations for adding, searching, deleting, and listing memories. The server handles file I/O operations and implements basic text-based storage, allowing AI systems to maintain persistent context across conversations without complex database setups. By focusing on simplicity and ease of use, this implementation enables quick deployment for scenarios requiring lightweight, file-based memory storage. It is particularly useful for chatbots, personal assistants, or any application where an AI needs to recall information from previous interactions.