Problem solved

Developers integrating AI models with external tools via MCP face challenges of token overhead, complex server management, and unreliable multi-step executions. NCP solves this by centralized orchestration that automatically discovers MCP servers, routes requests intelligently, and minimizes token usage, all while maintaining near-perfect accuracy and enabling reliable, stateful workflows.

Use cases

• Orchestrating multiple MCP servers for a single AI assistant to reduce token costs
• Building resumable AI workflows with state persistence and checkpointing
• Integrating cross-process events for real-time tool interactions
• Converting code into deployable Photon workflows (code-to-Photon)
• Managing and scaling MCP ecosystems in self-hosted environments

Audience

• Developers
• ML Engineers
• Data Scientists

Pros

• Intelligent MCP server discovery reduces manual configuration
• Significantly lowers token overhead, saving API costs
• Achieves 98.2% accuracy in orchestrating tool calls
• Supports stateful execution and checkpointing for complex workflows
• Open source and self-hosted for full control

Cons

• Requires understanding of MCP and server orchestration
• Limited community and ecosystem as a relatively new tool
• Potential integration challenges with non-standard MCP servers