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apcore-mcp

MCP and OpenAI Tools adapter for apcore modules

apcore-mcp projects registered apcore modules to MCP tool definitions and OpenAI-compatible JSON definitions. It maps schemas and behavioral annotations, supports JWT validation and elicitation-based approval, and keeps execution inside the apcore registry and policy path. Deployment security still depends on the operator's transport, identity, and authorization configuration.

· 01

Features

01Adapter Boundary: Expose registered modules without duplicating business logic
02Dual Support: Simultaneous exposure as MCP Server and OpenAI Tools
03JWT Authentication: Built-in secure token validation and identity injection
04Tool Explorer UI: Interactive browser-based testing and documentation suite
05Streaming Bridge: Real-time notification and chunk accumulation support
06User Elicitation: Interactive input requests during module execution
07Intelligent Conversion: Automated schema transformation and $ref inlining
08Annotation Mapping: Direct mapping of behavioral hints to MCP annotations
09Sanitized Execution: Secure error handling with AI suggestions and no leaks
10Dynamic Registration: Real-time module registration reflected in AI tools
· 02

Get Started

Python · Implementation

Python implementation of the apcore MCP adapter.

Install
$ pip install apcore-mcp
Quick Start
python.py
from apcore import Registry
from apcore_mcp import serve

# Auto-discover all modules
registry = Registry(extensions_dir="./extensions")
registry.discover()

# Start MCP server (stdio by default)
serve(registry)

# Or export as OpenAI tools
from apcore_mcp import to_openai_tools
tools = to_openai_tools(registry)
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