Okareo MCP Server

The Okareo MCP server exposes Okareo's evaluation capabilities as MCP tools, allowing AI coding assistants to create and manage scenarios, register models, run evaluations, and execute multi-turn…

Remote serverstreamable-http

What is the Okareo MCP Server?

Okareo is an MCP project maintained in the okareo-ai/okareo-mcp repository. The maintainer describes its purpose as “The Okareo MCP server exposes Okareo's evaluation capabilities as MCP tools, allowing AI coding assistants to create and manage scenarios, register models, run evaluations, and…”. Read the project documentation for the complete scope.

Hosted connection

The maintainer’s configuration uses https://tools.okareo.com/mcp. It declares streamable-http transport. Check the project’s account and authentication instructions when adding the endpoint to your client.

Source

Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

ToolWhat it does
save_scenarioSave a named scenario from rows of input/result data (idempotent)
list_scenariosList all scenarios in the project with names, IDs, and row counts
get_scenarioRetrieve a scenario's metadata and all data rows by name or ID
create_scenario_versionCreate a new version of an existing scenario with updated data
preview_delete_scenarioPreview what will be deleted before removing a scenario
delete_scenarioPermanently delete a scenario and all related test data
list_available_llmsBrowse available LLMs from the Okareo registry
register_generation_modelRegister a generation model for testing by selecting an LLM from the registry
list_generation_modelsList all registered generation models in the project
get_generation_modelRead detailed information about a registered generation model
update_generation_modelChange the LLM a registered generation model points to
delete_generation_modelRemove a registered generation model and all its related test data
list_checksList available quality checks (built-in and custom) for evaluating model outputs
run_testRun a quality test that evaluates a model against a scenario using specified checks
list_test_runsFind past test runs, most recent first. detail_level="summary" (default) or "detailed" for aggregate metrics
get_test_run_resultsLoad one page of a run's results by ID or name. detail_level="summary" (default) / "detailed" (per-check outcomes + explanations) / "full" (transcripts).…
get_conversation_transcriptRetrieve the full conversation transcript for a single data point
reevaluate_test_runRe-score a completed test run against a (possibly different) set of checks
create_or_update_checkCreate or update a quality check by name — model-based, code-based, or audio (upsert)
generate_checkGenerate a check from a natural-language description, then save it
get_checkRetrieve a check's full configuration, including its prompt template or code
delete_checkPermanently delete a check by name
calibrate_checkDry-run a draft check against a finished test run — per-row verdicts and the arguments the check received, saving nothing
create_or_update_targetCreate or update a Target — generation model, custom endpoint, or voice (OpenAI, Deepgram, Twilio)
get_targetRetrieve a Target's configuration by name (all types)
list_targetsFind simulation targets (voice and custom_endpoint). Bounded to 20 by default; name_contains filters
delete_targetRemove a simulation target and all its related test data
create_or_update_driverDefine a simulated user persona that will interact with your target
get_driverRetrieve a Driver's full configuration including the persona prompt
list_driversFind Driver personas. Bounded to 20 by default; name_contains filters
list_driver_voicesDiscover the voices, voice profiles, and languages available for voice drivers
run_simulationRun a multi-turn conversation evaluation. With based_on_run_id it inherits the original run's full configuration; any argument you pass overrides that one…
list_simulationsList past simulation runs with optional filters (target, scenario, limit)
ingest_conversationsSubmit completed voice conversations to Okareo for monitoring
connect_voice_integrationConnect a voice provider so its traffic flows into Okareo monitoring
list_voice_integrationsList the voice provider integrations in your project
get_voice_integrationRetrieve a voice provider integration by ID, including its status
update_voice_integrationUpdate a voice provider integration's metadata
rotate_voice_integration_secretRotate a voice provider integration's secrets
delete_voice_integrationDelete a voice provider integration by ID
get_voice_webhook_urlGet the inbound webhook endpoint for a voice provider
list_projectsList every project you can work in — id, name, tags, archive state — with the active one marked
select_projectChoose the project to work in for this conversation
create_projectCreate a new project
update_projectRename a project, or replace its tags
archive_projectHide a project from the project picker. Reversible; nothing is deleted
unarchive_projectRestore an archived project to the picker
clone_projectCopy an existing project's scenarios into a new project (dry-run first)
query_analyticsQuery Okareo's product analytics to understand evaluation trends
list_dashboardsList the analytics dashboards in your project
get_dashboardRetrieve a dashboard's full configuration by name
save_dashboardCreate or update an analytics dashboard by name (upsert)
reorder_dashboardsSet the display order of dashboards
delete_dashboardDelete a dashboard by name
list_tenantsList every Okareo organization you have access to in this MCP session
switch_tenantDoesn't change the active organization; returns how to reconnect and pick another one at sign-in
get_docsQuery the Okareo documentation system for conceptual or user-legible explanations
get_templatesRetrieve prompt templates for common Okareo patterns (works offline)
get_reps_baselineServe REPS agent-evaluation baseline material (scenario banks, drivers, checks, eval configs) from the latest tagged okareo-tools release

How to install the Okareo MCP Server

{
  "mcpServers": {
    "okareo": {
      "type": "http",
      "url": "https://tools.okareo.com/mcp"
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.