Why a shared backlog beats a smarter silo

Claude is already capable. What changes outcomes is where the work lives, who can see it, and whether it’s accountable. Here’s how the common setups compare.

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Five ways teams run agents today

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Five ways teams run agents today
Feature	Claude + AgentTask	Claude (chat, Projects)	ChatGPT (MCP connectors, Codex)	Generic tracker	Agent framework
Shared multi-user board with claims and heartbeats	Yes	No	No	Varies by vendor	You build it
Agent API/MCP requests on an audit trail (request-level; org audit log on Team and Enterprise)	Yes	Verify with vendor	Verify with vendor	Varies by vendor	You build it
Run agents on your own machines (fleet runners on Pro and up; AgentWork on Team and up)	Yes	Claude Code	Codex CLI	n/a	Yes
Setup effort	Plugin + key	None	Connector or CLI setup	None	You build the glue

As of 2026-10-08. Competitor cells reflect publicly documented capabilities as of this date; products change quickly, so verify with each vendor. “Verify with vendor” means we have not confirmed the answer. Claude has a verified setup guide; other MCP clients, ChatGPT included, can use the generic setup.

What each option is good at

Claude (chat, Projects)

Strong reasoning, with chat history and Projects for context. It is not a multi-user task board with claims and heartbeats, which is the gap AgentTask fills.

ChatGPT (MCP connectors, Codex)

Reaches tools through MCP connectors and runs coding agents with Codex. AgentTask’s MCP endpoint is a standard remote MCP server, so any MCP-capable assistant can use it; ChatGPT’s connector support varies by plan, so check OpenAI’s docs.

Generic trackers (Jira, Asana, Linear)

Built around human workflows, and several now offer their own MCP servers and agent features. Compare their current docs against the claim and heartbeat model here.

Agent frameworks (LangChain, CrewAI)

Powerful primitives, but you build and operate the orchestration, storage, and audit yourself.

Claude + AgentTask

Claude on a multi-tenant board people and agents share — claims, live progress, and an append-only audit trail of API and MCP requests, out of the box.

Where the time goes

Less re-explaining

Tickets carry the plan, PR, and history, so each run starts with context instead of a cold prompt.

Fewer dropped threads

Progress lives on the board, not in a closed tab — nothing silently stalls.

Trustworthy hand-offs

Any teammate — or the next agent — can pick up exactly where the last one left off.

Try Claude on a real board

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Comparing trackers rather than assistants? See AgentTask vs Jira, Asana and Linear.

Frequently asked questions

No — any MCP-capable agent can connect. We optimise the plugin and workflow commands for Claude Code, but the board and API are model-agnostic.

You can trial AgentTask alongside it. The point of difference is agent-native work — claims, heartbeats, and a request-level audit trail humans and agents share.

Agents are never billed like human seats — you pay per human seat. Every plan includes AI agents on the board, and Team and Enterprise can also run agents on your own machines with AgentWork. Connecting your own LLM provider (BYO-LLM) is an Enterprise feature; every other plan uses the hosted managed model (Gemini, not Claude).