"author:MCP-Mirror" matching MCP servers:

Enables execution of SuperCollider synth code through the Model Context Protocol using supercolliderjs, allowing AI assistants to generate and run audio synthesis programs.

Enables AI agents to interact with the Brex financial platform, allowing access to account information, transactions, expenses, receipts, budgets, and spend limits through the Brex API.

Enables AI assistants to interact with Joplin notes through full-text search, reading, creating, updating, and deleting notes, as well as importing markdown files directly into Joplin notebooks.

Provides comprehensive access to 471+ DigitalOcean API endpoints, enabling AI assistants to manage cloud infrastructure including droplets, databases, load balancers, DNS, Kubernetes, and other DigitalOcean resources programmatically.

Searches and fetches real-time documentation for libraries like Langchain, OpenAI, and Llama-Index using the Serper API. It allows LLMs to access up-to-date technical information and bypass knowledge cut-off limitations.

An MCP server for Infrastructure as Code that enables AI assistants to manage cloud resources through Ansible and Terraform operations. It supports executing playbooks, managing AWS services, and running Terraform commands with optional LocalStack integration.

Performs vulnerability scans using Trivy to generate Software Bill of Materials (SBOM) in CycloneDX format. It enables automated security auditing and dependency tracking through the Model Context Protocol.

Enables MCP host applications to retrieve and process structured documentation from user-defined llms.txt files. It provides tools to fetch specific URLs and audit the documentation context returned to the LLM.

Provides specialized backup and restoration capabilities for AI agents and code editors, enabling instant, context-aware save points for files and folders. It supports version history, pattern filtering, and automated safety backups to protect code during critical refactoring or restructuring tasks.

Enables AI assistants to execute AWS CLI commands and retrieve service documentation through the Model Context Protocol. It supports Unix pipes for output filtering and provides pre-defined prompt templates for common cloud management tasks.

Connects Claude Desktop directly to GitHub repositories and git commands, enabling users to clone repos, check status, commit changes, push code, create repositories, and manage GitHub resources through natural conversation.

An MCP server that enables LLMs to interact with Ashby's Applicant Tracking System for managing candidates, jobs, applications, and interviews. It supports data operations, batch processing, and access to pipeline analytics and reporting.

Routes MCP requests intelligently to multiple backend servers through a single gateway, bypassing tool limits by exposing only 2 routing tools while providing access to unlimited backend tools across services like GitHub, databases, and more.

Integrates Shaka Packager with Claude to enable video analysis, transcoding, and packaging for HLS and DASH streaming. It supports advanced features like DRM encryption and content conversion while working alongside the Filesystem MCP server to process local media files.

Enables AI assistants to interact with Testomat.io test management platform, allowing users to search and retrieve tests, test suites, test runs, and test plans using natural language queries with advanced filtering capabilities.

Provides detailed character analysis for text, counting total characters, characters without spaces, letters, numbers, and symbols through a simple MCP tool interface.

Implements a structured development workflow for LLM-based coding with feature clarification, PRD generation, phased development, and task tracking. Guides LLMs through organized feature development from requirements gathering to completion with document storage and progress monitoring.

Enables AI agents to dynamically discover and interact with APIs through Swagger/OpenAPI specifications and Postman collections using a strategic four-tool approach. It streamlines API integration by providing universal tools for endpoint discovery, detailed request information, and authenticated execution.

Enables seamless interaction with Azure DevOps for managing Git repositories, branches, and pull requests through natural language. It also supports automating and monitoring pipelines while providing secure, type-safe operations within MCP-compatible clients.

Enables complete Slack integration through natural language in Cursor IDE, supporting message sending, channel management, direct messaging, user lookup, reactions, and message search using the Slack API.