MCP Servers

Inbox Zero offers features such as: - AI Personal Assistant: Automates email management tasks like drafting replies, labeling, archiving, and forwarding. - Reply Zero: Tracks emails that require responses and those awaiting replies. - Bulk Unsubscriber: Enables quick unsubscribing from unwanted emails. - Cold Email Blocker: Automatically filters out unsolicited emails. - Email Analytics: Provides insights into email activity with various statistics. These tools aim to streamline email workflows and reduce time spent managing emails.

MCP-Google-Ads allows AI assistants to: - Account Management: List and access multiple Google Ads accounts. - Campaign Analytics: Retrieve campaign performance metrics, including impressions, clicks, conversions, and costs. - Keyword and Ad Performance: Analyze keyword effectiveness and ad copy performance. - Budget and Bid Management: Monitor budgets, analyze bid strategies, and identify optimization opportunities. - Custom Queries: Execute Google Ads Query Language (GAQL) queries for tailored data analysis. This integration enables AI-driven interaction with Google Ads, facilitating tasks such as campaign analysis and management through natural language commands.

MCP-Caiyun-Weather allows AI assistants to: - Real-Time Weather Data: Retrieve current weather conditions for specific locations. - Hourly Forecasts: Access weather forecasts for the next 72 hours. - Weekly Forecasts: Obtain daily weather forecasts for the upcoming 7 days. - Historical Weather Data: Fetch weather data from the past 24 hours. - Weather Alerts: Receive weather alerts for specific locations. This integration enables AI-driven interaction with Caiyun's weather services, facilitating tasks such as providing weather updates and forecasts through natural language commands.

Ashra MCP Server allows AI assistants to interact with Ashra's services through natural language commands. Key features include: - Service Integration: Facilitates communication between AI assistants and Ashra's platform. - Customizable Configuration: Supports environment-specific settings through configuration files. - Secure Access: Utilizes API keys for authenticated interactions.

DeepSeek MCP Server allows AI assistants to: - Model Selection: Choose between DeepSeek's R1 (deepseek-reasoner) and V3 (deepseek-chat) models. - Configuration Management: Adjust settings like temperature, max tokens, top P sampling, and penalties. - Multi-Turn Conversations: Maintain context across multiple interactions for coherent dialogues. - Automatic Fallback: Switch between models if the primary model is unavailable. This integration facilitates advanced AI-driven interactions through natural language commands.

K8M offers a streamlined interface for managing Kubernetes clusters, incorporating AI functionalities such as: - AI-Driven Insights: Utilizes integrated LLMs for tasks like resource explanation, YAML translation, and log analysis. - MCP Integration: Provides visual management of MCP tools, with 49 built-in tools enabling over 100 cluster operations. It can function as an MCP server for other LLM applications. - Multi-Cluster Management: Supports automatic detection and management of multiple clusters using kubeconfig. - Pod Management: Facilitates file operations within pods, real-time log viewing, and shell command execution. - CRD and Helm Support: Automatically discovers and manages Custom Resource Definitions (CRDs) and integrates with Helm for application deployment. These features make K8M a comprehensive tool for efficient and intelligent Kubernetes cluster management.

ForeverVM MCP Server allows AI assistants to: - Create Python REPLs: Instantiate persistent Python Read-Eval-Print Loops (REPLs) within ForeverVM sandboxes. - Execute Code: Run Python code within these REPLs, maintaining state across executions. This integration enables AI-driven code execution in secure, isolated environments, facilitating tasks such as code testing and evaluation through natural language commands.

E2B MCP Server (Python) allows AI assistants to run code snippets securely within a sandboxed environment. It integrates with clients like Claude Desktop, enabling natural language-driven code execution.

Linear MCP Server allows AI assistants to manage Linear issues through natural language commands. Key features include: - Issue Creation: Create new Linear issues with specified titles, descriptions, priorities, and statuses. - Issue Updates: Modify existing issues, including title, description, priority, and status changes. - Issue Search: Search for issues using flexible criteria such as text queries, team, status, assignee, labels, and priority. - User Issues Retrieval: Retrieve issues assigned to a specific user. - Comment Addition: Add comments to existing issues, supporting markdown formatting and optional custom user names and avatars.

LLM Context allows developers to inject relevant content from code or text projects into LLM chat interfaces. It utilizes .gitignore patterns for intelligent file selection and offers both a command-line clipboard workflow and direct LLM integration through MCP. Key features include: - Smart File Selection: Leverages .gitignore patterns to determine relevant files for context sharing. - Rule-Based Customization: Enables easy switching between different tasks, such as code review and documentation, through customizable rules. - Code Outlining: Provides smart code outlining to help LLMs understand the structure of the codebase. - Direct LLM Integration: Supports native integration with tools like Claude Desktop via MCP.

MCPDoc allows AI assistants to: - Documentation Access: Retrieve and process llms.txt files, which serve as indexes to detailed markdown documentation. - Integration with IDEs: Enhance development workflows by providing AI-driven access to documentation within IDEs like Cursor and Windsurf. - Customizable Sources: Support user-defined lists of llms.txt files for tailored documentation retrieval. This integration enables AI-driven interaction with structured documentation, facilitating tasks such as code assistance and information retrieval through natural language commands.

MCP-Neo4j provides an interface for AI assistants to execute graph queries, retrieve node and relationship details, and manage data within Neo4j databases using natural language commands.

MCP Web Research Server allows AI assistants to perform web searches and extract webpage content. Key features include: Google Search Integration: Perform Google searches and extract results. Webpage Content Extraction: Visit webpages and extract their content. Research Session Tracking: Maintain a list of visited pages, search queries, and other session details. Screenshot Capture: Capture screenshots of webpages. Note: As of February 13, 2025, this repository has been archived by the owner and is now read-only.

MCP-YouTube allows AI assistants to: - Subtitle Retrieval: Download subtitles from YouTube videos using yt-dlp. - Summarization: Provide concise summaries of YouTube video content. This integration enables AI-driven interaction with YouTube content, facilitating tasks such as video summarization through natural language commands.

MCP K8S Go allows AI assistants to perform various operations within a Kubernetes cluster, including: - Context Management: List available Kubernetes contexts. - Namespace Operations: List namespaces within the cluster. - Resource Handling: List and retrieve any Kubernetes resources, including pods, services, deployments, and custom resources. - Node Management: List nodes in the cluster. - Event Retrieval: Access Kubernetes events. - Pod Operations: Retrieve pod logs and execute commands within pods. This integration enables AI-driven interaction with Kubernetes environments, facilitating tasks such as resource monitoring and management through natural language commands.

Auto-generates APIs from SQL databases (Postgres, MySQL, etc.) for use with AI assistants. Supports REST, MCP, caching, and PII filtering.

MCP Proxy facilitates two primary modes of operation: - Stdio to SSE: Acts as a bridge for clients that communicate over stdio (e.g., Claude Desktop) to connect with remote MCP servers using SSE transport. This mode allows clients to interact with SSE-based servers without native SSE support. - SSE to Stdio: Exposes a local stdio MCP server as an SSE server, enabling remote clients to connect via SSE. In this mode, MCP Proxy listens for SSE requests, spawns the local stdio server, and manages the communication between them. These capabilities enhance the flexibility and interoperability of AI assistants and MCP servers across different transport protocols.

MCP-GSuite allows AI assistants to manage Gmail and Google Calendar using natural language. It supports reading and sending emails, managing drafts, and creating or deleting calendar events.