MCP Servers

AWS MCP allows AI assistants to query and manage AWS resources through natural language interactions. Key features include: - Natural Language Queries: Perform operations like listing EC2 instances, retrieving S3 bucket sizes, and identifying deployed Lambda functions using conversational commands. - Multi-Profile and SSO Support: Manage multiple AWS profiles and Single Sign-On (SSO) authentication seamlessly. - Multi-Region Operations: Execute commands across different AWS regions. - Secure Credential Handling: Utilizes local AWS credentials without exposing them to external services. - Local Execution: Runs locally, ensuring that your credentials and data remain secure. This integration streamlines AWS resource management by allowing conversational interactions with your AWS environment.

Claude Debugs For You facilitates interactive debugging sessions by connecting AI assistants with VS Code's debugging capabilities. Key features include: - Language Agnostic Debugging: Supports debugging across various programming languages, provided the language has debugger console support and a valid launch.json configuration in VS Code. - Interactive Expression Evaluation: Allows AI assistants to evaluate expressions and inspect variables during debugging sessions. - Seamless Integration: Works with MCP clients like Claude Desktop and Continue, enabling AI-driven debugging assistance. - Flexible Communication: Supports both standard input/output (stdio) and server-sent events (SSE) communication methods for compatibility with different MCP clients. This integration enhances development workflows by allowing AI assistants to assist in debugging tasks, providing insights, and suggesting fixes based on real-time code evaluation.

MCP Browser Use allows AI assistants to control web browsers using natural language commands. Key features include: - Browser Automation: Navigate pages, fill forms, and interact with elements via the runbrowseragent tool. - Visual Understanding: Optional screenshot analysis for vision-capable language models. - State Persistence: Manage browser sessions across multiple MCP calls or connect to a user's browser. - Multi-LLM Support: Integrates with providers like OpenAI, Anthropic, Google, and more. - Deep Research Tool: Conduct multi-step web research and generate reports using the rundeepsearch tool. This server enhances AI-driven web interactions, facilitating tasks like automated browsing, data extraction, and comprehensive web research.

MCP Server for Docker allows AI assistants to perform various Docker operations through natural language interactions, including: - Container Composition: Deploy and manage containers using descriptive commands. - Introspection and Debugging: Inspect and debug running containers. - Persistent Data Management: Handle Docker volumes for data persistence. This server is particularly useful for server administrators, tinkerers, and AI enthusiasts aiming to streamline Docker management through AI-driven interfaces.

Vite Plugin Vue MCP provides an MCP server for Vue applications, offering tools to access and manipulate the component tree, state, routes, and Pinia store. Key features include: - Component Tree Access: Retrieve and interact with the Vue component hierarchy. - State Management: Access and modify component and Pinia store states. - Routing Information: Retrieve details about the application's routing configuration. This integration facilitates enhanced development workflows by allowing AI models to comprehend and interact with the Vue app's structure and state.

Awesome Cursor MCP Server offers several AI-powered tools to enhance development within the Cursor editor: - Code Architect: Utilizes advanced reasoning LLMs to generate plans and instructions for coding agents. - Screenshot Buddy: Captures UI design screenshots for use with the composer agent. - Code Review: Triggers code reviews using git diffs. These tools aim to provide intelligent coding assistance, streamlining the development process.

Qdrant MCP Server provides a semantic memory layer for LLMs. It allows storing and querying embeddings via Qdrant’s vector engine. Texts and metadata can be added to collections and retrieved using semantic search. Compatible with Claude Desktop, Cursor, and other MCP clients.

MCP Send Email allows AI assistants to compose and send emails directly using the Resend API. Key features include: - Plain Text and HTML Emails: Supports sending both plain text and HTML-formatted emails. - Scheduling: Allows scheduling emails for future delivery. - CC and BCC Support: Enables adding CC and BCC recipients. - Reply-To Configuration: Allows setting custom reply-to addresses. - Customizable Sender Email: Supports customizable sender email addresses, requiring prior verification with Resend. This integration streamlines the process of sending emails directly from AI interfaces like Cursor or Claude Desktop, eliminating the need to copy and paste email content.

ElevenLabs MCP Server allows AI assistants to interact with ElevenLabs' APIs, providing features such as: - Speech Generation: Convert text to speech using ElevenLabs' advanced models. - Voice Cloning: Create custom voice profiles by cloning existing voices. - Audio Transcription: Transcribe audio files into text with high accuracy. The server supports integration with MCP clients like Claude Desktop, Cursor, Windsurf, and OpenAI Agents, facilitating seamless communication between AI assistants and ElevenLabs' services.

MCP-Unity allows AI assistants to perform various operations within the Unity Editor, including: - Menu Execution: Execute Unity menu items via the executemenuitem tool. - GameObject Selection: Select GameObjects in the scene hierarchy using select_gameobject. - Component Management: Add or update components on GameObjects with update_component. - Package Management: Install new packages using add_package. - Testing: Run tests with the run_tests tool. - Notifications: Display messages in the Unity Editor using notify_message. - Asset Management: Add assets to scenes with addassetto_scene. The server connects to the Unity Editor and communicates with AI assistants through MCP, facilitating seamless integration and control.

QGIS MCP facilitates two-way communication between AI assistants and QGIS Desktop, allowing operations such as: - Project Management: Create, load, and save QGIS projects. - Layer Manipulation: Add and remove vector or raster layers. - Processing Execution: Run processing algorithms from the QGIS Processing Toolbox. - Code Execution: Execute arbitrary Python code within QGIS. This integration enables AI-driven project creation, layer loading, and more, enhancing the capabilities of QGIS through AI assistance.

MCP Server Kubernetes allows AI assistants to perform various operations within a Kubernetes cluster, including: - Pod Management: List, create, describe, and delete pods. - Service and Deployment Management: List services, deployments, and nodes; update deployment replicas. - Namespace Operations: List and create namespaces. - Logging and Events: Retrieve logs from pods and get cluster events. - Helm Integration: Install, upgrade, and uninstall Helm charts with custom values and repository support. - Port Forwarding: Set up port forwarding to pods or services. - CronJob Management: Create, list, and describe cronjobs. The server connects to the current kubectl context, requiring kubectl and Helm v3 to be installed and properly configured.

OpenAPI MCP Server allows AI assistants to interact with OpenAPI specifications by: - Identifying the required OpenAPI identifier. - Requesting a summary in simple language. - Determining and explaining specific endpoints. This process facilitates understanding and utilizing complex APIs through natural language interactions.

JetBrains MCP Proxy Server facilitates seamless communication between AI assistants and JetBrains IDEs. It acts as a proxy, forwarding requests from clients to the IDE, enabling AI-driven code assistance and project navigation.

WCGW empowers AI assistants to perform coding and shell tasks directly on your local machine. It offers features like: Autonomous Execution: AI can execute shell commands and coding tasks. Interactive Command Handling: Supports interactive commands using arrow keys and other inputs. File Protections: Ensures AI reads a file before editing to prevent accidental overwrites. Shell Optimizations: Manages single shell instances to avoid rogue processes. Large File Editing: Supports incremental edits to large files, avoiding token limit issues. Syntax Checking: Provides feedback to the AI if edits contain syntax errors. These capabilities allow AI assistants to code, build, and run tasks locally, enhancing development workflows.

Nuxt MCP includes: - nuxt-mcp: A Nuxt module that injects MCP support into your Nuxt app. - vite-plugin-mcp: A Vite plugin to enable MCP capabilities in Vite projects. These tools allow LLMs to explore, analyze, and provide insights or code changes based on your project's structure and metadata.

IDA MCP Server enables AI assistants to interact with IDA Pro databases, providing tools to read and manipulate data via Large Language Models. It supports operations such as retrieving metadata, decompiling functions, disassembling code, and managing comments and variable names.

Basic Memory turns conversations with AI into persistent, local-first Markdown notes. It creates and navigates a linked knowledge graph, integrates with Obsidian, and supports multi-file memory, chunking, and metadata tagging — giving you full control and transparency over your data.