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docs(all): update README to clarify MCP challenges and solutions
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README.md

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@@ -19,14 +19,23 @@ DeployStack is **The First MCP-as-a-Service Platform**. We turn MCP from "comple
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## The Problem
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MCP is revolutionizing how AI agents use tools, but it has created a massive challenge for organizations:
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MCP changes how AI agents use tools, but it has created two critical challenges:
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### Problem 1: Management Chaos
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- **Credential Sprawl**: Developers copy and paste sensitive API keys and tokens into insecure local configuration files, creating a huge security risk.
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- **No Governance**: Who is using which tools? Which agent is accessing sensitive customer data? Without a central control plane, companies are blind.
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- **Developer Friction**: Developers spend hours managing complex configurations for dozens of tools, a process that is both tedious and error-prone. Onboarding a new developer is a nightmare of configuration management.
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- **Inconsistent Environments**: Every developer has a slightly different local setup, leading to "it works on my machine" problems and configuration drift.
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DeployStack was built to solve these problems head-on.
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### Problem 2: Context Window Consumption Crisis
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- **Token Bloat**: Each MCP server adds 5-15 tools to context. With 10 servers, that's 75,000+ tokens consumed before any work begins.
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- **Performance Degradation**: LLM accuracy drops significantly after 20-40 tools are loaded.
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- **Hard Limits**: Tools like Cursor enforce a 40-tool maximum, forcing developers to disable useful servers.
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- **Cannot Scale**: Teams hit performance walls when trying to use more than 5-8 MCP servers simultaneously.
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**Real-world example**: Claude Code users report 82,000 tokens (41% of context window) consumed by MCP tools at startup, leaving only 6% for actual work.
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DeployStack solves both problems with a complete MCP management platform and intelligent context window optimization.
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## 🚀 How It Works: A Quick Tour
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}
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```
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## Key Features
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### 🎯 Intelligent Context Window Optimization
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DeployStack includes a **hierarchical router** that reduces MCP token consumption by 90%+:
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**Traditional Approach:**
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- 10 MCP servers × 15 tools = 150 tools loaded
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- 150 tools × 500 tokens = 75,000 tokens consumed
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- Result: 37.5% of context window gone before you start
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**DeployStack Hierarchical Router:**
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- Exposes only 2 meta-tools: `discover_mcp_tools` and `execute_mcp_tool`
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- 2 tools × 175 tokens = 350 tokens consumed
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- Result: 0.175% of context window used
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- **Token Reduction: 99.5%**
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**How it works:**
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1. LLM calls `discover_mcp_tools(query)` - "Find GitHub tools"
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2. Router searches across all team MCP servers, returns relevant tool paths
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3. LLM calls `execute_mcp_tool(path, args)` with selected tool
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4. Router executes the actual MCP tool and returns results
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This means you can scale from 3 to 100+ MCP servers without degrading LLM performance.
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### 🚀 Zero Installation Experience
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**Before DeployStack:**
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```bash
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npm install -g some-mcp-cli
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some-mcp configure --api-key=xxx
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# Repeat for every tool, every developer
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```
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**After DeployStack:**
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```json
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{
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"mcpServers": {
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"deploystack": {
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"type": "http",
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"url": "https://satellite.deploystack.io/mcp"
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}
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}
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}
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```
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### 🔒 Enterprise Security & Governance
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- **Credential Vault**: Encrypted storage with automatic injection
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- **Team Isolation**: Complete separation between teams
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- **Audit Logging**: Track every tool interaction
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- **Role-Based Access**: Fine-grained permissions
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## Architecture: Two Ways to Deploy
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### Global Satellites (Managed by DeployStack)
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- **Zero Installation**: Just add URL to VS Code
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- **Context Optimization**: Hierarchical routing reduces token usage by 90%+
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- **Freemium Model**: Free tier with basic MCP servers
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- **Instant Access**: Pre-configured tools ready to use
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- **Multi-tenant**: Resource isolation between teams
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- **Example**: `https://satellite.deploystack.io/mcp`
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### Team Satellites (Deploy Your Own) - (On Premise or Cloud) - (Security Ready, Deployment Tooling Coming Soon)
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### Team Satellites (Deploy Your Own)
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- **Enterprise Security**: On-premise deployment within your network
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- **Internal Access**: Connect to company databases, APIs, file systems
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- **Complete Isolation**: Full team separation using Linux containers
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- **Same Performance**: Hierarchical routing reduces context consumption
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- **GitHub Actions Style**: Simple deployment with Docker
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- **Example**: `https://team-satellite.yourcompany.com/mcp`
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### **Phase 1: Foundation** (Completed)
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- **[Done]** Deployed `cloud.deploystack.io` hosted version with a robust backend and frontend
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- **[Done]** Deployed `cloud.deploystack.io` hosted version with backend and frontend
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- **[Done]** Implemented a secure user and team management system with roles and permissions
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- **[Done]** Integrated OAuth for secure logins (e.g., GitHub)
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- **[Done]** Created the initial MCP Server Catalog for tool discovery
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- **[Done]** Multi-User Configuration Management - support for multiple users within teams, each with personalized device-specific configurations
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- **[Done]** Advanced MCP Argument & Environment Variable Handling - comprehensive service layer with schema validation and runtime configuration assembly
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### **Phase 3: Satellite** (Current Priority)
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### **Phase 3: Satellite Infrastructure** (Completed)
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- **[Done]** **Global Satellite Infrastructure** - managed MCP servers via HTTPS
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- **[Done]** **Zero-Installation Experience** - just add URL to VS Code
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- **[Done]** **OAuth Authentication** - seamless token-based auth
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- **[Done]** **OAuth Authentication** - token-based auth
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- **[Done]** **Satellite Pairing Security** - JWT-based token registration system for secure satellite onboarding
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- **[Done]** **Public Launch** - production satellite for community use
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- **[Done]** **Resource Management** - process isolation (remote MCP) and limits
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- **[Done]** **GitHub README and Stars Integration** - automatic GitHub data fetching, secure storage, XSS prevention, DoS protection, and comprehensive audit logging for MCP server catalog enhancement
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- **[Done]** **Background Job Queue System** - complete 4-phase custom SQLite-based job queue with worker infrastructure, admin API, frontend monitoring UI, and comprehensive documentation for long-running tasks
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- **[Done]** **GitHub README and Stars Integration** - automatic GitHub data fetching, secure storage, XSS prevention, DoS protection, and audit logging for MCP server catalog enhancement
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- **[Done]** **Background Job Queue System** - complete 4-phase custom SQLite-based job queue with worker infrastructure, admin API, frontend monitoring UI, and documentation for long-running tasks
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- **[Done]** **Cron Job Scheduling System** - recurring task scheduler using node-cron with integration into the job queue system, standard cron expression support, automatic lifecycle management, and complete separation of scheduling logic from execution for reliability and monitoring
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- **[Done]** **Frontend Syntax Highlighting** - reusable CodeHighlight component with Prism.js for JSON, JavaScript, TypeScript, Bash, and YAML code blocks
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- **[Done]** **Resource Management** - process isolation (stdio) and limits
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- **[Done]** **MCP Registry** - integration of the official MCP Registry
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### **Phase 4: Context Window Optimization** (Current Priority - Next 30 Days)
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**Goal**: Reduce MCP token consumption by 90%+ through intelligent hierarchical routing
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- **[To Do]** **Hierarchical Router Implementation** - 2-tool pattern with `discover_mcp_tools` and `execute_mcp_tool`
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- **[To Do]** **Token Analytics Dashboard** - real-time monitoring of context window usage with before/after comparisons
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- **[To Do]** **Semantic Tool Search** - natural language queries across all installed MCP servers
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- **[To Do]** **Tool Discovery API** - return tool paths, descriptions, and estimated token costs
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- **[To Do]** **Smart Tool Execution** - route requests to correct backend server with credential injection
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- **[To Do]** **Performance Benchmarks** - measure and publish token reduction metrics (target: 90%+)
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- **[To Do]** **Optimization Recommendations** - suggest which servers to disable based on usage patterns
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- **[To Do]** **Documentation & Case Study** - technical deep-dive blog post with real-world metrics
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**Why This Matters**: Teams currently hit 40-tool limits and context overflow. This feature enables scaling from 3 to 100+ MCP servers without performance degradation.
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### **Phase 5: Advanced Governance** (Next 90 Days)
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- **[In Progress]** Build out Audit Logging features in the cloud UI
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- **[In Progress]** Develop Analytics dashboards for tool usage and performance
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- **[Done]** Develop Analytics dashboards for tool usage and performance
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- **[To Do]** Implement advanced policy controls (e.g., rate limiting, request validation)
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- **[To Do]** Enhance the searchable MCP Server Catalog within the cloud UI
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- **[Done]** Improve the searchable MCP Server Catalog within the cloud UI
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- **[To Do]** Deeper integration with IDEs and AI agent frameworks
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- **[To Do]** Per-team token budgets and cost attribution
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- **[To Do]** AI-powered tool recommendations based on conversation context
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### **Phase 4: Advanced Architecture** (Current Priority)
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### **Phase 6: Advanced Architecture** (Completed)
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- **[Done]** **Multi-Transport Support** - SSE, Streamable HTTP, Direct HTTP protocols
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- **[Done]** **Real-Time Command Orchestration** - instant status feedback
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- **[Done]** **Satellite Job System** - recurring background task management with JobManager, abstract BaseJob class, automatic error handling, execution metrics tracking, and extensible architecture for health checks, cleanup tasks, and periodic maintenance operations
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- **[Done]** **Satellite Backend Events System** - real-time event processing with convention-based auto-discovery handler pattern, batch processing (1-100 events), partial success handling, JSON schema validation per event type, and extensible architecture supporting MCP client connections, tool executions, server crashes, and custom event types
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- **[Done]** **MCP Client Activity Tracking** - personal dashboard feature tracking active MCP clients per user across all components (backend database with mcpClientActivity table, satellite in-memory tracker with 30-second background job reporting via event system, dashboard API endpoint with dual authentication and pagination, client name detection from OAuth/headers/user-agent)
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- **[Done]** **Time-Series Metrics System** - production-ready metrics infrastructure with 15-minute bucket aggregation, 3-day retention, automated cleanup
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- **[To Do]** **Comprehensive Monitoring** - satellite health and usage analytics
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- **[To Do]** **Enterprise Security** - audit logging and compliance features
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### **Phase 5: Enterprise Team Satellites** (Future)
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### **Phase 7: Enterprise Features** (Future)
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- **[To Do]** **Complete Monitoring** - satellite health and usage analytics
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- **[To Do]** **Enterprise Security** - advanced audit logging and compliance features
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- **[To Do]** **Team Satellites** - customer-deployed satellites for enterprise (*security infrastructure completed, deployment tooling pending*)
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- **[To Do]** **Advanced Team Isolation** - Linux namespaces and cgroups
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- **[To Do]** **On-Premise Deployment** - GitHub Actions runner-style deployment
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- **[To Do]** **Enterprise Authentication** - SSO integration (SAML, OIDC)
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### **Phase 6: Ecosystem Expansion** (Future)
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### **Phase 8: Ecosystem Expansion** (Future)
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- **[To Do]** Multi-region satellite deployment
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- **[To Do]** AI agent framework integrations
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- **[To Do]** Performance SLAs and guarantees
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- **[To Do]** SOC 2 Type II certification
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## Try DeployStack
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