Full-stack Model Context Protocol platform for building, testing, and deploying MCP servers and agentic AI applications
Secure & Govern Enterprise AI
Stage
Not given
Not given
Founded
Not given
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Based in
US
US
Pricing model
Freemium
Contact for pricing
Pricing
Hobby: free forever with 30k requests/mo; Pro: $30/org/mo with 300k requests/mo included and $0.10 per 1k extra requests beyond 300k; Enterprise: custom pricing starting at $250/mo with dedicated infrastructure and custom SLAs.
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Key features
Open-source TypeScript SDK with declarative decorators and Zod validation
NitroStudio desktop IDE for visual tool testing and AI reasoning visualization
NitroCloud serverless hosting with auto-scaling and custom domains
GitHub integration for one-click deployment
Enterprise authentication modules
White-label NitroChat AI interface
99.99% uptime SLA on NitroCloud
API to MCP conversion tools
Discover every AI model, agent and vendor across the enterprise
Govern AI policies mapped to NIST AI RMF, EU AI Act and ISO 42001
Prove compliance with real-time AI Cards and audit-ready attestation
AI Bill of Materials (AI-BOM) for complete system inventory
Third-party vendor AI assessment and continuous verification
SOC 2 Type 2 compliant and ISO 27001 certified
Continuous AI discovery and exposure mapping
What makes it different
Designed for teams building custom MCP tools from their own APIs, not a catalog of prebuilt connectors
Complete full-stack platform combining SDK, IDE, and cloud hosting in one suite
Open-source core with npm-installable packages for SDK, CLI, and UI widgets
80,000 deployments and 13 million requests already in production
Enterprise-grade security with AES-256 encryption and JWT authentication
One platform for the entire AI lifecycle instead of seven tools and seven dashboards
Independent vendor with no model to sell and no sides in the AI ecosystem
Trusted by Fortune 10 companies, global carriers and banks
Born from KPMG Studio with decades of combined AI and cybersecurity expertise
Continuous loop that automatically rediscovers and re-proves AI systems as they change