a && . .env && set +a && uv run evals/strict_match/test_strict_match.py ... Test ID: atlassian_agent_1 Prompt: show atlassian version Reference Trajectories: [['__start__', 'agent_atlassian']] Note: Shows the version of the Atlassian Server Version. ... Results: {'score': True} ... ``` #### Evaluation Results [Latest Strict Match Eval Results](evals/strict_match/README.md) --- ## 📜 License Apache 2.0 (see [LICENSE](./LICENSE)) --- ## 👥 Maintainers See [MAINTAINERS.md](MAINTAINERS.md) - Contributions welcome via PR or issue! --- ## 🙏 Acknowledgements - [LangGraph](https://github.com/langchain-ai/langgraph) and [LangChain](https://github.com/langchain-ai/langchain) for agent orchestration frameworks. - [langchain-mcp-adapters](https://github.com/langchain-ai/langchain-mcp-adapters) for MCP integration. - [AGNTCY Agent Connect Protocol(ACP)](https://docs.agntcy.org/pages/syntactic_sdk/connect.html) - [AGNTCY Agent Gateway Protocol(AGP)](https://docs.agntcy.org/pages/messaging_sdk/agp-howto.html) - [AGNTCY Workflow Server Manager (WFSM)](https://github.com/agntcy/workflow-srv-mgr) for deployment and orchestration. - [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) for the protocol specification. - [Google A2A](https://github.com/google/A2A/tree/main) - The open source community for ongoing support and contributions.25:T562,## What is Atlassian AI Agent? The Atlassian AI Agent is a powerful LLM-powered assistant designed to integrate with Atlassian products like Jira and Confluence, utilizing OpenAPI Codegen, LangGraph, and LangChain MCP Adapters. ## How to use Atlassian AI Agent? To use the agent, set up your environment by creating a `.env` file with necessary configurations, then start the workflow server in either ACP or A2A mode using the provided commands. ## Key features of Atlassian AI Agent? - 🤖 LLM-powered agent for managing Atlassian applications. - 🌐 Supports multiple protocols (ACP and A2A) for integration. - 🛡️ Secure access control with API token-based RBAC. - 🔌 Integrated communication with Atlassian MCP server. ## Use cases of Atlassian AI Agent? 1. Managing applications in Jira and Confluence. 2. Automating tasks such as creating, updating, and deleting applications. 3. Retrieving user information and application details. ## FAQ from Atlassian AI Agent? - Can the agent manage all Atlassian applications? > Yes, it can assist with various tasks across Jira and Confluence. - Is there a specific setup required to run the agent? > Yes, you need to configure environment variables and start the server in the desired mode. - What protocols does the agent support? > The agent supports both ACP and A2A protocols for flexible integration.26:T34bf,# Identity [![Lint](https://github.com/agntcy/identity/actions/workflows/lint.yml/badge.svg?branch=main)](https://github.com/marketplace/actions/super-linter) [![Contributor-Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-fbab2c.svg)](CODE_OF_CONDUCT.md)

Welcome to the Identity repository

--- **AGNTCY Identity** provides a secure and verifiable method to uniquely identify agents through open and decentralized techniques. Each agent is assigned a universally unique identifier, backed by verifiable credentials (VCs). **AGNTCY Identity** enables to bring your own identity using conventions like IDs assigned by Identity Providers (e.g., Okta) or Agent Cards (e.g., Google’s A2A), or be assigned an ID following standards (e.g., W3C DIDs). This component ensures that every agent in the **AGNTCY** ecosystem has a verifiable, universally unique identity, enabling secure authentication, trusted communication, and interoperability across diverse multi-agent systems, regardless of the identity assignm

#agntcy

🚀 Atlassian AI Agent

Identity