Partner Up, Build Smarter
Where every interface is AI-perceivable by design
Why AI Partner Up
Core principles that drive everything we build.
AI-Perceivable
Every module is inherently understandable by AI through enforced schemas — a design requirement, not an afterthought.
Open Source
Apache 2.0 licensed. Fully open, transparent, and community-driven.
Cross-Language
Language-agnostic specifications that any language can implement. Build in Python today, extend to Go or Rust tomorrow.
Schema-Driven
Strict input/output contracts on every interface. Predictable, validatable, and self-documenting.
Production Ready
Built for real-world use with built-in storage, monitoring, error recovery, and observability.
Extensible
Adapters for MCP, gRPC, HTTP, WebSocket, and more. Integrate with any protocol or framework.
Our Products
Three product lines — specification, AI bridge, and orchestration framework.
apcore
Schema-driven module development framework
Build modules that AI can truly understand. apcore enforces input_schema, output_schema, and description on every module, making interfaces inherently perceivable by AI.
- Schema-Driven
- AI-Perceivable
- Approval System
- Cross-Language Spec
apcore-mcp
Automatic MCP Server & OpenAI Tools Bridge
Turn any apcore-based project into a fully functional MCP Server and OpenAI-compatible tool provider — with zero code changes and zero configuration.
- Zero Configuration
- MCP + OpenAI Bridge
- Multi-Language Spec
- Auto-Discovery
apflow
Task orchestration framework for AI applications
Beyond simple task lists — orchestrate complex task trees with dependencies, priorities, and a unified execution interface across HTTP, SSH, Docker, gRPC, MCP, and LLM agents.
- Task Tree Orchestration
- Multi-Executor Ecosystem
- Built-in Task Scheduling
- A2A Protocol
apcore Ecosystem
Open-source adapters and integrations for popular frameworks.
flask-apcore
Turn your Flask endpoints into AI-understandable tools with simple decorators.
View on GitHub
Build AI-perceivable modules with your favorite tools. Our ecosystem projects provide seamless integration for various frameworks.
How They Work Together
Full-stack connectivity from framework integration to AI agents
[ Application Layer (Frameworks) ]
Django / Flask / NestJS / TipTap / Legacy Code
Relationship.layers.application.subcontent
[ Core Layer (APCore Registry) ]
Capability Discovery | Schema-Enforced Executor
( ACL | Middleware | Input/Output Validation )
[ Protocol Layer (Adaptation) ]
MCP <───> A2A <───> OpenAI Tools <───> CLI
Relationship.layers.protocol.subcontent
[ AI Layer (Agents) ]
LLM (Large Language Model)
( Compatible with leading models, powering AI Agents )
Ready to build AI-perceivable modules?
Start with apcore to define AI-perceivable modules, use apcore-mcp to bridge them to AI agents, or jump into apflow for task orchestration. All open source and production ready.