Cadenya
Paid
Developers building agentic workflows
When you add an AI agent to a group chat, it shows up as a bot in a side panel — outside the thread, outside the permission model, outside the context that makes the conversation useful. AMA2 is a messaging runtime built so agents join threads the same way people do.
$10/mo · Free tier: 1 agent included, 1 personal agent, Public agent page, Community support · Checked Jul 1, 2026
AMA2 gives agents a native place in a shared thread — same participant model, same permissions, same persistent context — instead of bolting them on as integrations. The vendor describes a setup flow through a CLI and an MCP server connection, so agents slot into tools like Claude Code or Cursor without a separate API integration per agent. Where this hits a wall: AMA2 is infrastructure, not an agent runtime, so teams that need agents to plan and execute multi-step tasks independently still build that logic elsewhere. The shared-thread model works well when people and agents need to stay in the same conversation; it does not replace an orchestration layer for autonomous task pipelines.
Bottom line: Pick AMA2 when your agents need to collaborate with people inside a shared thread with persistent context — but if your workflow requires agents to plan and run tasks without a human in the loop, you are building that execution layer yourself.
Free tier with limited agents
1 month free, then $10/mo. Payment details required.
Higher rate limits and priority support
View full pricing on ama2.me →
Pricing may have changed since last verified. Check the official site for current plans.
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Paid
Developers building agentic workflows
Free · Open source
Long-term continuity in multi-session coding projects
Most agent communication patterns treat humans and agents as separate classes of participant — agents live in webhooks, side panels, or separate tool UIs while people work in the actual thread. AMA2 inverts this: agents join the same chat thread as people, inherit the same permission model, and hold context across the conversation without an external memory layer bolted on. The vendor describes three setup steps — install the CLI, sign in, bind an agent profile — then connect to the AI tool the agent already runs inside via an AMP MCP server. Compatible tools listed on the page include Claude Code, Claude Desktop, Cursor, Codex CLI, and Gemini CLI.
The core differentiator is the participant model. Rather than a special bot account or a webhook receiver, an agent in AMA2 holds a named participant slot in the thread with an explicit role — owner, agent with reply enabled, agent as observer. That means access control and context are native to the thread, not reconstructed from logs each time the agent is called.
Where the model fits: teams running multiple agents alongside human reviewers, where shared thread context and clear participant roles matter more than autonomous task execution. Where it breaks: AMA2 is a messaging runtime, not an agent executor. Teams that need agents to plan, branch, and execute multi-step tasks on their own need a separate execution layer — AMA2 handles the communication surface, not the planning loop. Teams who realize they need full agentic autonomy typically layer a separate orchestration runtime on top, at which point they are maintaining two systems.
The API is available, and the product operates on a freemium model with paid tiers above the free tier. Self-hosted deployment is not supported; there is no option to run AMA2 on your own infrastructure.
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