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Unified Agent Protocol Core SDK - Universal interoperability layer for AI agents and tools

Project description

Unified Agent Protocol (UAP) – Core SDK Specification

Version: 0.1 Alpha
Maintained by: WhoMeta Labs part of WhoMeta Inc.
License: Apache 2.0
Language: Python 3.10+
Repository: Private/internal (planned public release Q3 2025)


✨ Introduction

The Unified Agent Protocol (UAP) is a foundational interoperability layer designed to standardize the definition, registration, execution, and orchestration of AI agents and tools across diverse ecosystems.
UAP is not a runtime or a competing protocol like A2A or MCP – instead, it acts as a universal adapter, enabling seamless translation between heterogeneous agent formats, toolkits, and interface protocols.

The uap-core SDK is the reference Python implementation of this protocol, designed for SDK-level integration, automatic conversions, and full schema introspection.


💡 Motivation

As the AI agent ecosystem evolves, developers face increasing friction when integrating tools across platforms like OpenWebUI, LangChain, Azure OpenAI Agents, OpenAPI-based agents, or proprietary agent chains.

Common challenges include:

  • ❌ Fragmented agent and tool definition formats
  • ❌ Missing bridges between proprietary agent runtimes
  • ❌ Lack of universal abstraction for tool metadata, input types, and execution capabilities
  • ❌ Friction when reusing agent definitions across platforms (e.g., MCP ↔ A2A ↔ OpenAPI)

UAP solves this by introducing a common schema + protocol that allows agents and tools to be described once – and deployed, registered, or bridged anywhere.


📦 Key Features (Milestone 1)

  • 🧠 Unified JSON model: All agent, tool, trigger, and role definitions follow a strongly typed Pydantic schema.
  • 🔌 Multi-source parsers:
    • parse_openwebui(json): Import tools from OpenWebUI format.
    • parse_langchain(tool): Extract tool metadata from LangChain definitions.
    • parse_openapi(spec): Map OpenAPI endpoints to UAP tools.
  • 📤 Export bridges:
    • to_a2a(agent): Generate A2A-compatible payload.
    • to_mcp(agent): Convert to Model Context Protocol (MCP) schema.
    • to_openapi(tool): Derive standard OpenAPI spec from UAP tool.
  • 🖥️ CLI (uap bind):
    • Run transformations via command-line: uap bind --input tools.json --format mcp
  • 🛠️ Development-first SDK:
    • Works offline, no server required.
    • Fully typed Python models (intellisense, validation).
    • Optional integration with LangChain, FastAPI, and asyncio runtimes.

🧩 Core Concepts

Concept Description
Tool Describes an executable unit with input/output schemas and runtime hints.
Agent A logical actor using one or more tools to fulfill a task or objective.
Trigger Defines when and how agents/tools should activate (event, cron, intent).
Role Describes access & behavioral context (e.g., "analyst", "investigator").
OutputSchema Optional structure for results / downstream usage.
UIConfig Describes how this entity is represented in GUIs (forms, widgets, prompts).

All objects are implemented as subclasses of pydantic.BaseModel and support:

  • ✅ Full JSON validation
  • .dict() / .json() / .from_json() compatibility
  • ✅ Versioning fields
  • ✅ Extension-safe typing (e.g., extra = "allow")

🔄 Ecosystem Bridges

Target Protocol Bridge Status Description
A2A (Agent-to-Agent) to_a2a() Convert UAP agent into valid A2A descriptor
MCP (Model Context Protocol) to_mcp() Map UAP agent/tool into MCP-compliant schema
OpenAPI 3 to_openapi() Export UAP tool(s) as OpenAPI endpoints

These bridges allow inter-protocol operability – for example, developers can register a LangChain tool on OpenWebUI and then expose it in an A2A runtime via UAP translation.


📚 Example Use Case

# Convert OpenWebUI tools into MCP-ready format
uap bind --input tools_openwebui.json --format mcp > mcp_payload.json

🤝 Contributing

Contributions, issues and feature requests are very welcome!

  1. Fork the repository
  2. Create your feature branch (git checkout -b feat/awesome-feature)
  3. Commit your changes (git commit -m 'feat: add awesome feature')
  4. Push to the branch (git push origin feat/awesome-feature)
  5. Open a pull request

For full guidelines, please read the CONTRIBUTE guide.


⚖️ License

This project is licensed under the Apache License 2.0 – see the LICENSE file for details.


📑 Changelog

All notable changes will be documented in CHANGELOG.md.

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