{"apiVersion":"v1","directorySlug":"simtooreal-mcp-5e89eb9154","title":"SIMTOOREAL","description":"Train robot policies in Isaac Lab & MuJoCo. Auto-tune stalled runs, close the sim-to-real gap with Bayesian DR calibration, and deploy safely. Free plan.","pageUrl":"https://www.mcpbundles.com/skills/simtooreal-mcp-5e89eb9154","connectPath":"importable","connectAction":"import_server","catalogListing":false,"bundleSlug":null,"listingKind":"remote_mcp","kind":"provider","transportUrl":"https://www.simtooreal.com/mcp","hostedMcpUrl":null,"toolCount":8,"toolInventoryStatus":"observed","refreshedAt":"2026-11-03T13:26:00.516172+00:00","registryName":"com.simtooreal/simtooreal-mcp-5e89eb9154","registryVersion":"2026.11.3","registryEligible":true,"tools":[{"name":"call_api","description":"Call any SIMTOOREAL backend REST endpoint. Use this to query runs, metrics, system info, artifacts, training status, fleet, deployments, marketplace, etc. The backend has ~100 routes under /api/v1/.","inputSchema":{"type":"object","required":["method","path"],"properties":{"body":{"type":"object"},"path":{"type":"string"},"method":{"enum":["GET","POST","PATCH","DELETE"],"type":"string"},"auth_token":{"type":"string"}}},"logicalName":"call_api","displayName":"call_api","title":"call_api","annotations":{"untrustedContentHint":true,"readOnlyHint":true}},{"name":"analyze_run","description":"Fetch a training run's metrics and logs then use AI to generate a detailed analysis: progress summary, reward trends, stability observations, and recommendations.","inputSchema":{"type":"object","required":["run_id"],"properties":{"run_id":{"type":"string"},"auth_token":{"type":"string"}}},"logicalName":"analyze_run","displayName":"analyze_run","title":"analyze_run","annotations":{"untrustedContentHint":true,"readOnlyHint":true}},{"name":"diagnose_failure","description":"Fetch failure events and logs for a run then use AI to identify root causes and suggest specific fixes.","inputSchema":{"type":"object","required":["run_id"],"properties":{"run_id":{"type":"string"},"auth_token":{"type":"string"}}},"logicalName":"diagnose_failure","displayName":"diagnose_failure","title":"diagnose_failure","annotations":{"untrustedContentHint":true,"readOnlyHint":true}},{"name":"suggest_hyperparams","description":"Analyze a completed run's config and metrics then use AI to suggest better hyperparameters for the next training run with reasoning for each change.","inputSchema":{"type":"object","required":["run_id"],"properties":{"run_id":{"type":"string"},"auth_token":{"type":"string"}}},"logicalName":"suggest_hyperparams","displayName":"suggest_hyperparams","title":"suggest_hyperparams","annotations":{"untrustedContentHint":true,"readOnlyHint":true}},{"name":"robot_move","description":"Send a motion command to a real deployed robot unit in the fleet. Supports joint-space commands (list of angles in radians) or Cartesian end-effector targets (x,y,z + optional quaternion). Use fleet_status first to confirm the unit is online before commanding it. The command is forwarded to the robot's onboard controller via the deployment telemetry channel.","inputSchema":{"type":"object","required":["unit_id","command_type"],"properties":{"unit_id":{"type":"string"},"auth_token":{"type":"string"},"command_type":{"enum":["joint_positions","cartesian_pose","gripper","stop","home"],"type":"string"},"speed_factor":{"type":"number","default":0.3},"gripper_width":{"type":"number"},"cartesian_pose":{"type":"object","properties":{"x":{"type":"number"},"y":{"type":"number"},"z":{"type":"number"},"qw":{"type":"number"},"qx":{"type":"number"},"qy":{"type":"number"},"qz":{"type":"number"}}},"joint_positions":{"type":"array","items":{"type":"number"}}}},"logicalName":"robot_move","displayName":"robot_move","title":"robot_move","annotations":{"untrustedContentHint":true,"readOnlyHint":true}},{"name":"fleet_status","description":"Get real-time status of all robot fleet units: online/offline, current policy version, task success rate, fault codes, and last telemetry timestamp. Use this before sending robot_move commands to verify the target unit is online and healthy.","inputSchema":{"type":"object","properties":{"unit_id":{"type":"string"},"auth_token":{"type":"string"}}},"logicalName":"fleet_status","displayName":"fleet_status","title":"fleet_status","annotations":{"untrustedContentHint":true,"readOnlyHint":true}},{"name":"seed_fault_retrain","description":"Create a fault-aware VLA fine-tuning job seeded from fleet unit fault codes. Collects recent fault events from the specified unit, builds a curated training config that targets the observed failure modes, then enqueues a fine-tune job. This implements the Failure→Retrain loop: fleet fault codes → auto-seed fine-tune → deploy fix.","inputSchema":{"type":"object","required":["unit_id"],"properties":{"unit_id":{"type":"string"},"model_id":{"type":"string","default":"act"},"demo_path":{"type":"string"},"max_steps":{"type":"integer","default":500},"auth_token":{"type":"string"},"output_name":{"type":"string"}}},"logicalName":"seed_fault_retrain","displayName":"seed_fault_retrain","title":"seed_fault_retrain","annotations":{"untrustedContentHint":true,"readOnlyHint":true}},{"name":"get_visual_divergence","description":"Compute or retrieve the sim-vs-real visual divergence score for a deployment. Returns per-channel SSIM, color histogram divergence, edge density ratio, and domain adaptation suggestions (lighting range, texture randomization, camera settings). High scores (>0.4) indicate the sim visuals differ significantly from real cameras — use the suggestions to update domain randomization config.","inputSchema":{"type":"object","required":["deployment_id"],"properties":{"auth_token":{"type":"string"},"deployment_id":{"type":"string"},"sim_frame_url":{"type":"string"},"real_frame_url":{"type":"string"}}},"logicalName":"get_visual_divergence","displayName":"get_visual_divergence","title":"get_visual_divergence","annotations":{"untrustedContentHint":true,"readOnlyHint":true}}],"toolSource":"directory_preview","agentAction":"both","installLinks":[{"id":"cursor","label":"Cursor","href":"cursor://anysphere.cursor-deeplink/mcp/install?name=SIMTOOREAL&config=eyJ1cmwiOiAiaHR0cHM6Ly93d3cuc2ltdG9vcmVhbC5jb20vbWNwIn0%3D"},{"id":"vscode","label":"VS Code","href":"vscode:mcp/install?%7B%22name%22%3A%22SIMTOOREAL%22%2C%22type%22%3A%22http%22%2C%22url%22%3A%22https%3A%2F%2Fwww.simtooreal.com%2Fmcp%22%7D"},{"id":"vscode-insiders","label":"VS Code Insiders","href":"vscode-insiders:mcp/install?%7B%22name%22%3A%22SIMTOOREAL%22%2C%22type%22%3A%22http%22%2C%22url%22%3A%22https%3A%2F%2Fwww.simtooreal.com%2Fmcp%22%7D"},{"id":"claude-web","label":"Claude.ai","href":"https://claude.ai/customize/connectors?modal=add-custom-connector&connectorName=SIMTOOREAL&connectorUrl=https%3A%2F%2Fwww.simtooreal.com%2Fmcp"},{"id":"codex","label":"Codex","copyText":"codex mcp add \"SIMTOOREAL\" --url \"https://www.simtooreal.com/mcp\""},{"id":"chatgpt","label":"ChatGPT","href":"https://www.mcpbundles.com/docs/integrations/chatgpt"}],"catalogUrl":"https://www.mcpbundles.com/api/directory/v1/servers/simtooreal-mcp-5e89eb9154","callUrl":"https://www.mcpbundles.com/api/directory/v1/servers/simtooreal-mcp-5e89eb9154/tools/{tool}","mcpServerUrl":"https://www.simtooreal.com/mcp","liveCatalogUrl":"https://www.mcpbundles.com/api/directory/v1/servers/simtooreal-mcp-5e89eb9154?live=1"}