Okareo
Agent simulation and evaluation for voice and text agents — run dozens of synthetic conversations against your agent from inside Claude Code, Cursor, or any MCP-ready editor.
The Okareo MCP server turns your AI coding assistant into an evaluation and testing workbench. Instead of writing SDK scripts or switching to a dashboard, you describe what you want in natural language and your copilot does the rest: build synthetic users from your codebase, run multi-turn simulations against your agent, and pull back transcripts, traces, and scores for analysis.
Okareo is hosted — there's nothing to install and nothing to run locally. Point your editor at the endpoint, sign in once through your browser, and the tools appear.
https://tools.okareo.com/mcp
What you can do from a prompt
- Generate Drivers from your code. Okareo reads your agent's system prompt, tools, and policy logic and proposes synthetic users (Drivers) that stress the parts most likely to break — not generic personas.
- Run voice and text simulations in parallel. Spin up dozens of synthetic callers across languages, run them against your target, and get results back in moments.
- Replay production failures as tests. Pull a failed call from a connected voice integration, turn it into a reusable Driver, and add it to your suite.
- Evaluate and re-score. Run judge, symbolic, and audio-based checks; re-score a past run against a new check without re-running the model.
- Query analytics. Trend pass rates across models and pin dashboards.
Why Okareo
- Voice depth. Synthetic callers across many languages, with the noise, crosstalk, and clipping real customers call from.
- One timeline, three views. Simulation transcript, observability trace, and audio land together — so Conversation Designers and Engineers debug the same call.
- Agent-first, multi-turn-first. The unit of evaluation is a full conversation, not a single prompt/response pair.
Supported editors
Claude Code · Claude Desktop · Cursor · VS Code 1.101+ · Cline · Gemini Code Assist · GitHub Copilot · Windsurf — and any client that speaks MCP's streamable-HTTP transport.
Connect
Claude Code (one line):
claude mcp add --transport http okareo https://tools.okareo.com/mcp
Any MCP client (config):
{
"mcpServers": {
"okareo": {
"type": "http",
"url": "https://tools.okareo.com/mcp"
}
}
}
Authentication
OAuth on first connect — a browser tab opens to app.okareo.com, you sign in and consent, and your editor stores the token. If your client doesn't yet implement MCP OAuth discovery, set OKAREO_API_KEY in your environment and use the Bearer-header fallback (see the docs).
Example prompts
- "Run my refund scenarios against the voice agent in Spanish and Portuguese. Show me what regressed."
- "Pull this week's calls where the language switch failed and turn them into Drivers."
- "Re-score last night's evaluation against my new pii_leak check without re-running the model."
- "Read my agent in src/ and create 12 Drivers that stress the policy boundaries, then run them."
Tools
- Scenarios:
save_scenario,list_scenarios,get_scenario,create_scenario_version - Drivers:
create_or_update_driver,list_driver_voices,get_driver,list_drivers - Targets:
create_or_update_target,get_target,list_targets - Simulations:
run_simulation,list_simulations - Tests & results:
run_test,list_test_runs,get_test_run_results,get_conversation_transcript,reevaluate_test_run - Checks:
create_or_update_check,generate_check - Voice:
ingest_conversations,connect_voice_integration,get_voice_webhook_url - Models & analytics:
list_available_llms,register_generation_model,query_analytics,save_dashboard
Links
- Docs: https://docs.okareo.com/mcp/introduction
- Configuration: https://docs.okareo.com/mcp/configuration
- Website: https://okareo.com/mcp
- GitHub: https://github.com/okareo-ai/okareo-mcp
- Python SDK: https://pypi.org/project/okareo/
- TypeScript SDK: https://www.npmjs.com/package/okareo-ts-sdk
服务器配置
{
"mcpServers": {
"okareo": {
"type": "http",
"url": "https://tools.okareo.com/mcp"
}
}
}