Full-stack Model Context Protocol platform for building, testing, and deploying MCP servers and agentic AI applications
Open-source AI agent orchestration platform for incident response and automation
Stage
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Founded
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Based in
US
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Pricing model
Freemium
Open source
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
Incident response with agent investigation and pull request generation
Automated workflows triggered on schedules or webhooks
Agent summoning from GitHub, GitLab and Radicle with /ryph command
Semantic memory system for shared and persistent agent learning
Credentials kept behind gateways with no access in sandbox
Customized environments per repository with cached dependencies
Browser use for agent interactions with live watching
Artifacts and pages for reports and overviews
Deployment options from laptop to Kubernetes
Tool proxy with allowlisted MCP server integrations
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
Agents work without holding real credentials or keys
Changes ship as patches that require review before merge
Runs on your own infrastructure from laptop to cloud
Semantic memory learns across runs with deduplication and contradiction handling
Built-in safety assuming agents can be manipulated or exploited
NitroStack
Ryph