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
Overview
What is Smart AI Bridge?
Smart AI Bridge is a production-ready Model Context Protocol (MCP) server designed to orchestrate AI-powered development operations across multiple backends, featuring automatic failover, intelligent routing, and advanced error prevention capabilities.
How to use Smart AI Bridge?
To use Smart AI Bridge, install the necessary dependencies, configure your local and cloud AI backends, and run the server using the provided command. You can then send requests to the server for various AI tasks.
Key features of Smart AI Bridge?
- Multi-AI backend orchestration with a pre-configured 4-backend system.
- Intelligent routing based on task complexity and content analysis.
- Advanced fuzzy matching to reduce errors and improve response accuracy.
- Comprehensive toolset for file operations, code review, and validation.
- High security with a score of 9.7/10, including DoS protection and input validation.
Use cases of Smart AI Bridge?
- Automating coding tasks with specialized AI backends.
- Performing complex mathematical analysis and research.
- Processing large files and extensive documentation efficiently.
- Enhancing game development with AI-driven insights and optimizations.
FAQ from Smart AI Bridge?
- Can Smart AI Bridge integrate with any AI provider?
Yes! It supports various AI providers including OpenAI, Anthropic, and custom APIs.
- Is Smart AI Bridge secure?
Yes! It has a high security score and includes multiple protective measures.
- How can I extend the backend capabilities?
You can follow the EXTENDING.md guide to add unlimited backends.
Server Config
{
"mcpServers": {
"smart-ai-bridge": {
"command": "node",
"args": [
"smart-ai-bridge.js"
],
"cwd": ".",
"env": {
"LOCAL_MODEL_ENDPOINT": "http://localhost:1234/v1",
"CLOUD_API_KEY_1": "your-cloud-api-key-1",
"CLOUD_API_KEY_2": "your-cloud-api-key-2",
"CLOUD_API_KEY_3": "your-cloud-api-key-3"
}
}
}
}Project Info
Created At
8 months agoUpdated At
8 months agoAuthor Name
Platano78Star
-Language
-License
-Category
developer-tools
Recommend Servers
View AllAirtreks Mcp
@SEKeener
a day ago
Test
@modelcontextprotocol
test
6 months ago
Sigstore
@3089464667
a day ago
Tavily Mcp
@tavily-ai
JavaScript
a year ago