The apex behavioral-simulation engine,now callable from inside any agent.
Aetherya simulates audience cognition before launch. The Aetherya MCP exposes that power as tools, so any AI agent or coding tool can test a site, a headline, or an idea against a synthetic audience without leaving the editor.
Aetherya, now as
MCP tools.
Point any MCP-capable agent at a site or a piece of copy and it gets behavioral feedback from a synthetic audience, including predicted friction, hesitation, drop-off, and messaging clarity, all without leaving the editor.
Note · Results are simulated. Every signal comes from a synthetic audience and predicted behavior, not real-user data.
One protocol, every editor
Claude Code, Cursor, Windsurf, Codex, Pi, OpenCode, Gemini CLI, and Antigravity. If it speaks MCP, it speaks Aetherya.
Behavior, not heuristics
Findings are grounded in simulated cognition, showing how an audience would think, hesitate, and decide.
Audiences you control
Describe a segment in plain language and target it across every tool in the catalog.
Inside the loop
Your agent gets evidence it can act on before a human ever reviews the work.
One synthetic audience.
The full surface of the protocol. Every tool runs against a simulated audience and returns predicted behavior, evidence your agent can act on.
aetherya_audit_siteRun a behavioral simulation of a URL: predicted UX friction, hesitation, drop-off, and messaging-clarity issues with concrete fixes.
aetherya_get_audit_resultFetch an audit's findings by job_id. Audits run async, so poll this while a simulation is still running.
aetherya_list_audiencesList your synthetic audiences, the simulated personas you can target.
aetherya_create_audienceGenerate new synthetic personas from a plain-language description, e.g. "first-time SaaS buyers in Germany".
aetherya_test_copyTest a headline, value-prop, or copy variant against a synthetic audience for predicted clarity and response.
aetherya_ask_audiencePose an open-ended question to a synthetic audience ("would this confuse people?") and get a predicted, in-character response.
Where your agent uses it.
Behavioral simulation, folded into the work your agent already does, before the decision, before the spend, before launch.
Your agent audits a page it just built and resolves the top predicted friction before you ever see it.
Your agent A/B-tests ad copy against a simulated audience before a single dollar of spend.
Your agent spins up a target audience from a description, then simulates a launch page against it.
Your agent asks a synthetic segment whether a value prop lands, answered in their own words.
Install via npm.
The only supported install path is the published @aetherya/mcp package on npm, run with npx. Add it to your MCP client, then run the discovery-first auth flow.
claude mcp add aetherya -- npx -y @aetherya/mcp
npx -y @aetherya/mcp auth{
"mcpServers": {
"aetherya": {
"command": "npx",
"args": ["-y", "@aetherya/mcp"],
"env": {}
}
}
}On first use, the MCP client discovers Aetherya metadata and opens a human claim ceremony. The user reviews the workspace and exact capabilities at /claim. Legacy API keys remain available from Settings → API Keys for existing integrations; they start with aeth_live_. npx pulls @aetherya/mcp from npm and runs it on demand, so it stays current automatically.