Jira connector for AI agents
Connect your AI agent to Jira with 134 production-ready actions via MCP, A2A, SDK, CLI, or API.
StackOne AI Agent Actions
for Jira.
134 production-ready actions for your agent to do more on Jira.
Make your Jira agents perform.
Every Jira action runs on Falcon.
Falcon, StackOne's execution engine, makes your agents fast, accurate, and reliable.
Explore Falcon Engine88.7% attack detection accuracy.
Built in the StackOne platform.
StackOne Defender scans and classifies every Jira payload before it reaches your agent, with precision and latency no other solution can match.
Do More, Build Less.
Managed Integration Infrastructure for Jira AI Agents.
200+ Connectors. 10,000+ Actions.
Access integrations via API, AI SDKs, MCP & A2A.
Pre-built authentication UI.
Enterprise-Ready architecture.
"What impressed us most about StackOne is its ambition and clarity. They're creating infrastructure that modern software and the entire AI agent ecosystem can rely on. The depth of secure integrations, the pace of delivery, and the team's foresight into AI's future uniquely position StackOne to redefine this category."
Luna Schmid, Partner at GV
"We've been impressed by how quickly and deeply StackOne integrates with complex enterprise systems -- and now, with their focus on agent-to-agent interoperability, they're unlocking even more powerful use cases for customers. StackOne delivers all of the above in a universal layer -- without compromise."
Barbry McGann, SVP at Workday Ventures
Resources
Learn How to Improve Agentic Performance.
Unified API Limitations for AI Agent Integration: 7 Ways They Break
Unified APIs work for traditional software but fail AI agents in specific, measurable ways. Here are 7 problems we found after building both approaches, with examples from Workday, Greenhouse, Jira, and Salesforce.
14 minAgentic Context Engineering: Why AI Agents Kill Their Own Context Windows
AI agents exceed their context windows without knowing it. Six failure patterns and seven survival architectures for agentic context engineering.
15 minMCP Code Mode: Keeping Tool Responses Out of Agent Context
Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.
11 minComparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery
Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.
10 minMore integrations
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Put your AI agents to work
All the tools you need to build and scale AI agents integrations, with best-in-class security & privacy.