Create README.md

README.md

@@ -15,179 +15,367 @@ tags:
 - gradio-6
 license: mit
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+🧠 OmniMind Orchestrator
+Automated MCP Server Generation for Enterprise Workflows
 
-# OmniMind Orchestrator
+OmniMind turns natural language descriptions into fully working MCP (Model Context Protocol) servers.
+You describe the integration you want, and OmniMind designs, generates, and wires up the MCP server for you.
 
-**Automated MCP Server Generation for Enterprise Workflows**
+“Create a tool that checks if a domain is available for registration”
+→ OmniMind generates the MCP server, handles the API integration, and prepares it for deployment — in ~30 seconds.
 
-## Competition Entry
+🎯 Competition Entry
+Track: MCP in Action – Enterprise Category
 
-**Track**: MCP in Action - Enterprise Category
-**Event**: MCP's 1st Birthday Hackathon (Anthropic & Gradio)
-**Tags**: `mcp-in-action-track-enterprise`
+Event: MCP’s 1st Birthday Hackathon (Anthropic & Gradio)
 
----
+Tag: mcp-in-action-track-enterprise
 
-## What It Does
+🎥 Demo
+Loom Walkthrough: Watch the OmniMind Orchestrator demo
 
-OmniMind generates custom MCP (Model Context Protocol) servers from natural language descriptions. Instead of manually writing integration code, you describe what you need and the system generates the code, deploys it, and makes it available as a tool.
+(Shows real-time generation of an MCP server for live crypto data and other enterprise-style workflows.)
 
-**Example**:
-You say: *"Create a tool that checks if a domain is available for registration"*
-OmniMind writes the MCP server code, handles the API integration, and deploys it. Takes about 30 seconds.
+🌐 Problem & Vision
+Enterprise teams increasingly want MCP-native tools to connect LLMs to:
 
----
+internal APIs,
 
-## Key Features
+third-party SaaS,
 
-### 1. Dynamic Code Generation
-- Generates complete MCP server implementations
-- Includes API integration, error handling, and documentation
-- Uses Claude Sonnet 4 for code synthesis
+data warehouses and transactional systems.
 
-### 2. Multi-Model Routing
-- Routes tasks to appropriate models based on requirements
-- Claude Sonnet 4 for complex reasoning and code
-- Gemini 2.0 Flash for faster, simpler tasks
-- GPT-4o-mini for planning and routing decisions
-- Reduces API costs by ~90% vs using Claude for everything
+But today, every integration still looks like a mini engineering project:
 
-### 3. Performance Optimization
-- Analyzes generated code for improvements
-- Suggests and applies optimizations automatically
-- Benchmarks show 10-25% performance gains on average
+custom boilerplate,
 
-### 4. Voice Interface (Optional)
-- ElevenLabs integration for voice input/output
-- Useful for hands-free operation in field/manufacturing settings
+careful error handling,
 
-### 5. Enterprise Knowledge Integration
-- LlamaIndex RAG for context from company documents
-- Generates more accurate code when given domain knowledge
+model context wiring,
 
----
+deployment plumbing.
 
-## Technical Architecture
-
-```
-User Request
-    ↓
-Multi-Model Router (selects appropriate LLM)
-    ↓
-Code Generation (creates MCP server)
-    ↓
-Optional: Modal Deployment (serverless hosting)
-    ↓
-Execution & Response
-```
-
-**Stack**:
-- **Frontend**: Gradio 6.0
-- **LLMs**: Claude Sonnet 4, Gemini 2.0 Flash, GPT-4o-mini
-- **Deployment**: Modal (optional)
-- **RAG**: LlamaIndex
-- **Voice**: ElevenLabs (optional)
+OmniMind Orchestrator aims to compress that effort from hours → seconds, while still keeping a human in the loop for review and security.
 
----
+⚙️ What OmniMind Does
+OmniMind takes a plain-language spec like:
 
-## Use Cases
+“Create a tool that fetches real-time stock prices from Alpha Vantage and returns OHLC data for a given symbol.”
 
-**API Integration**
-*"Create a tool that fetches real-time stock prices from Alpha Vantage"*
+and automatically:
 
-**Data Processing**
-*"Build a tool that converts CSV files to JSON with schema validation"*
+Plans the MCP server structure (tools, parameters, schema).
 
-**Web Scraping**
-*"Make a tool that extracts product prices from an e-commerce site"*
+Selects models for planning, codegen, and optimization via a multi-model router.
 
-**Internal Tools**
-*"Create a tool that queries our PostgreSQL database for customer orders"*
+Generates code for a fully functional MCP server.
 
----
+Integrates APIs (including auth, error handling, and basic validation).
+
+Optionally deploys via Modal for serverless hosting.
+
+Exposes the server as an MCP tool ready to be used by compatible clients.
+
+🔑 Key Features
+1. Dynamic MCP Code Generation
+Generates complete MCP server implementations from natural language.
+
+Handles:
+
+API calls and integration logic
+
+basic error handling and retries
+
+inline documentation & comments
+
+Uses Claude Sonnet 4 for high-quality code synthesis and reasoning-heavy steps.
+
+2. Multi-Model Routing for Cost & Latency
+OmniMind doesn’t throw every request at the biggest model. Instead, it uses a router to pick the right model for the job:
+
+Claude Sonnet 4 – complex reasoning, core code generation, refactors.
+
+Gemini 2.0 Flash – fast responses for simple transforms and scaffolding.
+
+GPT-4o-mini – lightweight planning, routing, and glue logic.
+
+This strategy:
+
+Offloads simple subtasks to cheaper/faster models.
+
+Reserves premium models for only the hardest parts.
+
+Cuts API costs by ~90% compared to “Claude everywhere” while maintaining quality.
+
+3. Performance-Aware Code Generation
+Once a server is generated, OmniMind can:
+
+Analyze the code for obvious performance issues.
+
+Suggest improved patterns (e.g. batching, caching, connection reuse).
+
+Regenerate sections of code to apply optimizations.
+
+Benchmarks on sample integrations show 10–25% performance gains on average for optimized versions, especially on I/O-bound workflows.
+
+4. Optional Voice Interface
+For hands-free or field environments (manufacturing, operations, etc.):
+
+ElevenLabs integration for:
+
+Voice input → text → MCP codegen request.
+
+Text output → synthesized speech.
+
+Makes it possible to say:
+
+“Create a tool that checks inventory levels in our warehouse API”
+and have the system handle it end-to-end.
+
+5. Enterprise Knowledge Integration (RAG)
+Enterprise integrations usually depend on tribal knowledge:
+
+internal API conventions,
+
+auth patterns,
+
+environment-specific edge cases.
+
+OmniMind uses LlamaIndex for RAG over:
+
+internal documentation,
+
+API specs,
+
+runbooks and design docs.
+
+This allows it to:
+
+Ground code generation in company-specific context.
+
+Reduce hallucinations about endpoints and parameters.
+
+Generate more accurate, domain-aligned integrations.
+
+🧱 System Overview
+text
+Copy code
+User (text or voice)
+        │
+        ▼
+ Multi-Model Router ──► chooses Claude / Gemini / GPT-4o-mini
+        │
+        ▼
+  Planning & Spec Expansion
+        │
+        ▼
+   Code Generation Engine
+        │
+        ▼
+  (Optional) Performance Pass
+        │
+        ▼
+  (Optional) Modal Deployment
+        │
+        ▼
+   MCP Server Available as Tool
+Core layers:
+
+UX Layer: Gradio 6 app (Hugging Face Space) in app.py.
+
+Routing Layer: Decides which LLM handles which part of the workflow.
+
+Codegen Layer: Synthesizes MCP server code from natural language + context.
+
+Knowledge Layer (RAG): Pulls enterprise docs via LlamaIndex.
+
+Deployment Layer (optional): Wraps servers for deployment on Modal.
+
+Voice Layer (optional): ElevenLabs for speech I/O.
+
+💼 Example Use Cases
+1. API Integration
+“Create a tool that fetches real-time stock prices from Alpha Vantage.”
+
+OmniMind:
+
+Generates MCP tools that:
+
+accept ticker symbol and interval,
+
+call Alpha Vantage,
 
-## Setup
+normalize and return the data in MCP-friendly schemas.
 
-### Required API Keys
-- Anthropic Claude: [Get key](https://console.anthropic.com/settings/keys)
-- OpenAI: [Get key](https://platform.openai.com/api-keys)
-- Google Gemini: [Get key](https://aistudio.google.com/app/apikey)
+2. Data Processing & Transformation
+“Build a tool that converts CSV files to JSON with schema validation.”
 
-### Optional API Keys
-- Modal (for deployment): [Get token](https://modal.com/settings)
-- ElevenLabs (for voice): [Get key](https://elevenlabs.io/app/settings)
+OmniMind:
 
-Configure in Space Settings → Variables and secrets:
-```
+Designs tool parameters (file_path, schema, etc.).
+
+Generates code for:
+
+reading CSV,
+
+validating against a simple schema,
+
+returning JSON with validation errors if any.
+
+3. Web Scraping
+“Make a tool that extracts product prices from an e-commerce site.”
+
+OmniMind:
+
+Generates scraping logic (using a library you specify or generic requests/HTML parsing).
+
+Handles user-specified:
+
+base URL,
+
+CSS selectors / patterns,
+
+pagination options.
+
+(Subject to the target site’s ToS and legal constraints — still needs human review.)
+
+4. Internal Enterprise Tools
+“Create a tool that queries our PostgreSQL database for customer orders.”
+
+OmniMind:
+
+Generates code to:
+
+connect to Postgres with environment variables,
+
+execute safe parameterized queries,
+
+return summarized results.
+
+This is where LlamaIndex + internal docs really matter (e.g. schema names, auth patterns).
+
+🧰 Tech Stack
+Frontend
+
+Gradio 6.0 – main orchestrator UI (hosts on Hugging Face Spaces).
+
+LLMs
+
+Anthropic Claude Sonnet 4 – deep reasoning and high-quality codegen.
+
+Google Gemini 2.0 Flash – fast inference for simpler subtasks.
+
+OpenAI GPT-4o-mini – planning, routing, and smaller logic steps.
+
+Infrastructure & Extras
+
+Modal – optional serverless deployment of generated MCP servers.
+
+LlamaIndex – retrieval-augmented generation over enterprise docs.
+
+ElevenLabs – optional voice in/out.
+
+MCP – target protocol for the generated servers.
+
+🔐 Setup
+Required API Keys
+Anthropic Claude – Get key
+
+OpenAI – Get key
+
+Google Gemini – Get key
+
+Optional Keys
+Modal (deployment) – Get token
+
+ElevenLabs (voice) – Get key
+
+On Hugging Face Spaces, configure them under
+Settings → Variables and secrets:
+
+bash
+Copy code
 ANTHROPIC_API_KEY=sk-ant-xxx
 OPENAI_API_KEY=sk-xxx
 GOOGLE_API_KEY=xxx
-```
+MODAL_TOKEN=xxx          # optional
+ELEVENLABS_API_KEY=xxx   # optional
+💸 Cost Comparison (Back-of-the-Envelope)
+Traditional Integration
+Developer time: 4–8 hours @ ~$100/hr → $400–800
 
----
+Testing & debugging: 2–4 hours → $200–400
 
-## Cost Comparison
+Total: ≈ $600–1,200 per integration
 
-**Traditional Development**:
-- Developer time: 4-8 hours @ $100/hr = $400-800
-- Testing & debugging: 2-4 hours = $200-400
-- **Total**: $600-1,200 per integration
+With OmniMind Orchestrator
+Code generation: ≈ 30 seconds
 
-**With OmniMind**:
-- Generation time: 30 seconds
-- API cost: ~$0.05
-- **Total**: $0.05 per integration
+API cost (multi-model routed): ≈ $0.05
 
-*Note: Still requires human review of generated code for production use.*
+Total: ≈ $0.05 per integration (plus human review time)
 
----
+⚠️ Important: OmniMind does not remove the need for human review. Generated code for production systems should always be audited.
 
-## Limitations & Honest Assessment
+🚧 Limitations & Honest Assessment
+Works well for:
 
-**What works well**:
-- Generating standard API wrappers and data transformations
-- Creating simple automation tools
-- Rapid prototyping of integrations
+Standard API wrappers and adapters.
 
-**What needs improvement**:
-- Complex business logic requires human review
-- Security-critical code should be manually audited
-- Performance optimization is hit-or-miss
-- No guarantee of correctness (LLM limitations apply)
+Data transformation tools and utility MCP servers.
 
-**This is a prototype**, not production-ready software. Use it for:
-- Prototyping
-- Internal tools
-- Non-critical automations
+Rapid prototyping and internal tooling.
 
-Don't use it for:
-- Financial transactions
-- Healthcare/safety-critical systems
-- Anything where bugs could cause serious harm
+Exploring what MCP-based automation could look like in your stack.
 
----
+Still needs improvement / human oversight for:
 
-## Sponsor Integrations
+Complex, multi-step business logic.
 
-This project uses:
-- **Anthropic Claude**: Code generation and reasoning
-- **Google Gemini**: Fast task routing and multimodal support
-- **OpenAI GPT-4**: Planning and decision-making
-- **Modal**: Optional serverless deployment
-- **LlamaIndex**: Enterprise knowledge retrieval
-- **ElevenLabs**: Optional voice interface
-- **Gradio 6**: User interface
+Security-sensitive operations (auth, permissions, financial operations).
 
----
+Advanced performance tuning beyond obvious optimizations.
 
-## License
+Fully correct behavior across all edge cases (LLM limitations still apply).
 
-MIT License - See LICENSE file for details
+Intended usage:
 
----
+✅ Prototyping
+
+✅ Internal tools
+
+✅ Non-critical automations
+
+Not recommended for:
+
+❌ Financial transactions and trading logic
+
+❌ Healthcare / safety-critical systems
+
+❌ Scenarios where bugs could cause serious harm or large financial loss
+
+🤝 Sponsor & Partner Integrations
+This project showcases integrations with:
+
+Anthropic Claude – core code generation and reasoning.
+
+Google Gemini – fast routing and multimodal support.
+
+OpenAI GPT-4 – planning and decision logic.
+
+Modal – optional serverless deployment target.
+
+LlamaIndex – enterprise knowledge retrieval.
+
+ElevenLabs – voice interface.
+
+Gradio 6 – user-facing interface and hackathon demo environment.
 
-## Acknowledgments
+📜 License
+This project is licensed under the MIT License.
+See the LICENSE file for full details.
 
-Thanks to Anthropic, Gradio, and HuggingFace for hosting this hackathon and providing the infrastructure to build this.
+🙏 Acknowledgments
+Thanks to Anthropic, Gradio, and Hugging Face for organizing MCP’s 1st Birthday Hackathon and providing the infrastructure to build and demo this project.
 
-Built for MCP's 1st Birthday Hackathon - November 2024
+Built for MCP’s 1st Birthday Hackathon – November 2024.