Sponsored by Deepsite.site

Tag

#tools

538 results found

MCP-MESSENGER

**SlashMCP** is a production-grade AI workspace that connects LLMs to real-world data and tools through an intuitive chat interface. Built on the Model Context Protocol (MCP), it enables seamless interaction with multiple AI providers (OpenAI, Claude, Gemini) while providing powerful capabilities for document analysis, financial data queries, web scraping, and multi-agent workflow orchestration. ### Key Features: - **Multi-LLM Support**: Switch between GPT-4, Claude, and Gemini at runtime—no restart needed - **Smart Command Autocomplete**: Type `/` to discover and execute MCP server commands instantly - **Document Intelligence**: Drag-and-drop documents with automatic OCR extraction and vision analysis - **Financial Data Integration**: Real-time stock quotes, charts, and prediction market data via Alpha Vantage and Polymarket - **Browser Automation**: Web scraping and navigation using Playwright MCP - **Multi-Agent Orchestration**: Intelligent routing with specialized agents for command discovery, tool execution, and response synthesis - **Dynamic MCP Registry**: Add and use any MCP server on the fly without code changes - **Voice Interaction**: Browser-based transcription and text-to-speech support ### Use Cases: - Research and analysis workflows - Document processing and extraction - Financial market monitoring - Web data collection and comparison - Multi-step task automation **Live Demo:** [ slashmcp.vercel.app ]( https://slashmcp.vercel.app ) **GitHub:** [ github.com/mcpmessenger/slashmcp ]( https://github.com/mcpmessenger/slashmcp ) **Website:** [ slashmcp.com](https://slashmcp.com )

Smart Ai Bridge

Smart AI Bridge is a production-ready Model Context Protocol (MCP) server that orchestrates AI-powered development operations across multiple backends with automatic failover, smart routing, and advanced error prevention capabilities. Key Features 🤖 Multi-AI Backend Orchestration Pre-configured 4-Backend System: 1 local model + 3 cloud AI backends (fully customizable - bring your own providers) Fully Expandable: Add unlimited backends via EXTENDING.md guide Intelligent Routing: Automatic backend selection based on task complexity and content analysis Health-Aware Failover: Circuit breakers with automatic fallback chains Bring Your Own Models: Configure any AI provider (local models, cloud APIs, custom endpoints) 🎨 Bring Your Own Backends: The system ships with example configuration using local LM Studio and NVIDIA cloud APIs, but supports ANY AI providers - OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, custom APIs, or local models via Ollama/vLLM/etc. See EXTENDING.md for integration guide. 🎯 Advanced Fuzzy Matching Three-Phase Matching: Exact (<5ms) → Fuzzy (<50ms) → Suggestions (<100ms) Error Prevention: 80% reduction in "text not found" errors Levenshtein Distance: Industry-standard similarity calculation Security Hardened: 9.7/10 security score with DoS protection Cross-Platform: Automatic Windows/Unix line ending handling 🛠️ Comprehensive Toolset 19 Total Tools: 9 core tools + 10 intelligent aliases Code Review: AI-powered analysis with security auditing File Operations: Advanced read, edit, write with atomic transactions Multi-Edit: Batch operations with automatic rollback Validation: Pre-flight checks with fuzzy matching support 🔒 Enterprise Security Security Score: 9.7/10 with comprehensive controls DoS Protection: Complexity limits, iteration caps, timeout enforcement Input Validation: Type checking, structure validation, sanitization Metrics Tracking: Operation monitoring and abuse detection Audit Trail: Complete logging with error sanitization 🏆 Production Ready: 100% test coverage, enterprise-grade reliability, MIT licensed 🚀 Multi-Backend Architecture Flexible 4-backend system pre-configured with 1 local + 3 cloud backends for maximum development efficiency. The architecture is fully expandable - see EXTENDING.md for adding additional backends. 🎯 Pre-configured AI Backends The system comes with 4 specialized backends (fully expandable via EXTENDING.md): Cloud Backend 1 - Coding Specialist (Priority 1) Specialization: Advanced coding, debugging, implementation Optimal For: JavaScript, Python, API development, refactoring, game development Routing: Automatic for coding patterns and task_type: 'coding' Example Providers: OpenAI GPT-4, Anthropic Claude, Qwen via NVIDIA API, Codestral, etc. Cloud Backend 2 - Analysis Specialist (Priority 2) Specialization: Mathematical analysis, research, strategy Features: Advanced reasoning capabilities with thinking process Optimal For: Game balance, statistical analysis, strategic planning Routing: Automatic for analysis patterns and math/research tasks Example Providers: DeepSeek via NVIDIA/custom API, Claude Opus, GPT-4 Advanced, etc. Local Backend - Unlimited Tokens (Priority 3) Specialization: Large context processing, unlimited capacity Optimal For: Processing large files (>50KB), extensive documentation, massive codebases Routing: Automatic for large prompts and unlimited token requirements Example Providers: Any local model via LM Studio, Ollama, vLLM - DeepSeek, Llama, Mistral, Qwen, etc. Cloud Backend 3 - General Purpose (Priority 4) Specialization: General-purpose tasks, additional fallback capacity Optimal For: Diverse tasks, backup routing, multi-modal capabilities Routing: Fallback and general-purpose queries Example Providers: Google Gemini, Azure OpenAI, AWS Bedrock, Anthropic Claude, etc. 🎨 Example Configuration: The default setup uses LM Studio (local) + NVIDIA API (cloud), but you can configure ANY providers. See EXTENDING.md for step-by-step instructions on integrating OpenAI, Anthropic, Azure, AWS, or custom APIs. 🧠 Smart Routing Intelligence Advanced content analysis with empirical learning: // Smart Routing Decision Tree if (prompt.length > 50,000) → Local Backend (unlimited capacity) else if (math/analysis patterns detected) → Cloud Backend 2 (analysis specialist) else if (coding patterns detected) → Cloud Backend 1 (coding specialist) else → Default to Cloud Backend 1 (highest priority) Pattern Recognition: Coding Patterns: function|class|debug|implement|javascript|python|api|optimize Math/Analysis Patterns: analyze|calculate|statistics|balance|metrics|research|strategy Large Context: File size >100KB or prompt length >50,000 characters

Docker Mcp Server

Docker MCP Server A comprehensive Model Context Protocol (MCP) server that provides advanced Docker operations through a unified interface. This server combines 16 powerful Docker MCP tools with 25+ convenient CLI aliases to create a complete Docker workflow solution for developers, DevOps engineers, and system administrators. 🌟 What Makes Docker MCP Server Special Docker MCP Server is not just another Docker wrapper - it's a complete Docker workflow enhancement system designed to make Docker operations more intuitive, secure, and efficient: 🎯 Unified Interface MCP Protocol Integration: Seamlessly works with MCP-compatible tools and IDEs CLI Convenience: 25+ carefully crafted aliases for common Docker workflows Consistent API: All operations follow the same patterns and conventions Cross-Platform: Full support for Linux, macOS, and Windows environments 🔒 Security-First Design Docker-Managed Security: All password operations handled by Docker daemon for maximum security Zero Password Exposure: Passwords never appear in command history, process lists, or arguments Token Authentication Support: Full support for Personal Access Tokens and service accounts Registry Flexibility: Secure login to Docker Hub, AWS ECR, Azure ACR, Google GCR, and custom registries CI/CD Security: Secure stdin password input for automated deployment pipelines Permission Management: Proper handling of Docker daemon permissions and credential storage 🚀 Developer Experience Comprehensive Help System: Every command includes detailed documentation with --help Smart Defaults: Sensible default configurations for common use cases Error Prevention: Built-in safety checks and confirmation prompts for destructive operations Rich Output: Formatted, colored output with clear status indicators 📊 Advanced Operations Complete Container Lifecycle: From build to publish with comprehensive registry support Multi-Container Management: Docker Compose integration with service orchestration Registry Publishing: Advanced image publishing with multi-platform support and automated workflows Network & Volume Management: Advanced networking and storage operations System Maintenance: Intelligent cleanup tools with multiple safety levels Development Workflows: Specialized commands for development environments