RQM Jobs MCP

Last 30 days

Uptime

100%

Response time

772 ms typical, 838 ms slowest 5%

Last check

27 min ago

Next check

in 6 h

How to call it

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "rqm-jobs-mcp": {
      "type": "http",
      "url": "https://jobs.rqmtechnologies.com/mcp"
    }
  }
}

39 tools

• describe_quantum_capabilities

  Free, anonymous API-owned scientific capability contracts and domain suggestions. Start here before choosing or funding a quantum job. Inspect separate source, installed, hosted, simulator, live-QPU and public coverage; unknown means unverified. Read schemas, examples and limits;

• run_account_job

  Purchase one discovered service using prepaid credits within the account owner's saved spending policy. First search_buyer_jobs for the task and inspect the selected request_schema, required inputs, limits, examples and evidence boundaries. Use its buyer service_id as capability_

• get_account_job

  Read this agent's saved account-funded job by its returned job ID to check status and recover available result and receipt. Use after submission or when following up on an existing purchase; acceptance is not completion. Report the saved state and only available results, with the

• list_account_jobs

  List up to 100 recent jobs for this agent, or find the original account-funded purchase using its idempotency key. Use for purchase history and recovery before retrying an uncertain submission; use list_buyer_jobs or search_buyer_jobs for available services. Omit the key for rece

• list_buyer_jobs

  Return complete agent discovery contracts and readiness for the exact 20/20/20 RQM specialist work portfolio.

• search_buyer_jobs

  Select RQM buyer jobs from work-language requests using deterministic semantic scoring over instructions, examples, outputs, and next steps.

• list_capabilities

  Describe the preserved v0/v1 surface or the dynamic v2/v3 Wave catalog.

• get_capability

  Return one full approved public Wave capability descriptor.

• run_buyer_job

  Quote, settle, and submit one allowlisted WaveEngine, Studio, or Robotics buyer job using x402.

• settle_buyer_job

  Server-side Jobs-rail x402 settle for connector hosts that cannot sign. Replays the same idempotency key with PAYMENT-SIGNATURE. An RQM-owned operator signer is not external revenue.

• robotics_frame_convention_validation_v1

  Problem: Validate this bounded frame graph and report unit, axis, handedness, rotation, and transform-direction violations. Input: JSON with frames, declared length unit, declared transform direction, declared.... Result: pass, fail, or unsupported verdict, exact findings, normal

• robotics_assess_calibration_quality_v1

  Problem: Assess this bounded calibration dataset against the supplied residual, coverage, and consistency rules. Input: JSON with length unit, observations, rules. Result: pass, fail, or indeterminate verdict, residual metrics, per-rule evaluations. Limits: Software/model evidenc

• robotics_diagnose_trajectory_instability_v1

  Problem: Diagnose this bounded trajectory for the supplied oscillation, divergence, and stability indicators. Input: JSON with frame id, length unit, samples, rules. Result: pass, fail, or unsupported verdict, indicator series, violation windows. Limits: Software/model evidence o

• robotics_validate_trajectory_timing_v1

  Problem: Validate timestamps, ordering, rates, gaps, and synchronization in this bounded trajectory or sensor trace. Input: JSON with clock id, samples, rules. Result: pass or fail verdict, normalized timeline, exact timing defects. Limits: Software/model evidence only; 65536 req

• robotics_normalize_sensor_frames_v1

  Problem: Convert these bounded sensor observations into the supplied target frame and unit convention. Input: JSON with frame graph, target frame id, observations. Result: normalized or unsupported verdict, normalized observations, transform paths. Limits: Software/model evidence

• robotics_reconstruct_smoothed_trajectory_v1

  Problem: Reconstruct this bounded trajectory under the supplied smoothing model and residual rule. Input: JSON with samples, model, rules. Result: smoothed trajectory, residual RMSE, caller-rule verdict. Limits: Software/model evidence only; 65536 request bytes; 5 s execution.

• robotics_estimate_fused_state_v1

  Problem: Fuse these bounded synchronized sensor observations under the supplied diagonal uncertainty model and rules. Input: JSON with observations, model, rules. Result: fused state, diagonal covariance, sensor residuals and verdict. Limits: Software/model evidence only; 65536 r

• robotics_compute_actuator_alignment_correction_v1

  Problem: Compute a bounded actuator alignment correction from these observations and caller acceptance limits. Input: JSON with observations, model, rules. Result: correction parameters, pre/post residuals, applicability verdict. Limits: Software/model evidence only; 65536 reques

• robotics_compare_controller_responses_v1

  Problem: Compare these bounded controller responses on identical traces using the supplied objective rules. Input: JSON with baseline, candidate, rules. Result: metric values, threshold verdicts, difference series. Limits: Software/model evidence only; 65536 request bytes; 5 s ex

• robotics_compare_state_estimators_v1

  Problem: Compare these bounded estimator outputs against the supplied reference and objective rules. Input: JSON with reference, estimators, rules. Result: per-estimator metrics, rule verdicts, deterministic selected estimator or.... Limits: Software/model evidence only; 65536 re

• robotics_compare_planned_observed_trajectories_v1

  Problem: Compare planned and observed trajectories against caller tolerances. Input: JSON with planned, observed, rules. Result: typed verdict, measured metrics, candidate only when verified. Limits: Software/model evidence only; 65536 request bytes; 5 s execution.

• robotics_compare_digital_twin_observations_v1

  Problem: Compare digital-twin output with mapped observations against caller tolerances. Input: JSON with predicted, observed, declared mapping, rules. Result: typed verdict, measured metrics, candidate only when verified. Limits: Software/model evidence only; 65536 request bytes

• robotics_tune_controller_to_objectives_v1

  Problem: Tune a supported controller only within supplied bounds and safety limits. Input: JSON with supported controller, current gain, fixture error, target error.... Result: typed verdict, measured metrics, candidate only when verified. Limits: Software/model evidence only; 65

• robotics_optimize_trajectory_to_constraints_v1

  Problem: Optimize a bounded trajectory only when speed and duration constraints pass. Input: JSON with trajectory, maximum speed, maximum duration s. Result: typed verdict, measured metrics, candidate only when verified. Limits: Software/model evidence only; 65536 request bytes;

• robotics_validate_kinematic_dynamic_limits_v1

  Problem: Accept or reject a bounded trajectory against caller kinematic limits. Input: JSON with trajectory, maximum speed, maximum acceleration. Result: typed verdict, measured metrics, candidate only when verified. Limits: Software/model evidence only; 65536 request bytes; 5 s

• robotics_optimize_disturbance_rejection_v1

  Problem: Tune supported control parameters against this bounded disturbance model and supplied response objectives. Input: JSON with mass, damping, disturbance, time step seconds, baseline kp, baseline.... Result: candidate parameters, comparative metrics and constraint results.

• robotics_validate_closed_loop_stability_v1

  Problem: Accept or reject this bounded closed-loop model under the supplied stability criteria. Input: JSON with discrete state matrix, criteria. Result: eigenvalues, spectral radius and rule results. Limits: Software/model evidence only; 65536 request bytes; 5 s execution.

• robotics_check_collision_constraints_v1

  Problem: Check this bounded geometry and trajectory against the supplied collision and clearance constraints. Input: JSON with trajectory, obstacles, robot radius, minimum clearance. Result: clearance, collision candidates and constraint results. Limits: Software/model evidence o

• robotics_replay_workcell_trace_v1

  Problem: Replay this bounded workcell trace against the supplied event assertions. Input: JSON with model id, events, assertions. Result: timeline, assertion results and trace digest. Limits: Software/model evidence only; 65536 request bytes; 5 s execution.

• robotics_analyze_force_disturbance_response_v1

  Problem: Analyze these bounded force and disturbance inputs against the supplied response model and criteria. Input: JSON with mass kg, damping n s per m, stiffness n per m, time step seconds.... Result: modeled response, metrics and rule results. Limits: Software/model evidence

• quote_job

  Return a preserved v0 placeholder or a durable v1 Account Core USD quote.

• get_account_balance

  Read the authenticated canonical Account Core prepaid USD balance.

• create_funding_session

  Create an idempotent Stripe Checkout URL for human prepaid funding.

• submit_wave_job

  Reserve an exact quote and submit one bounded catalog-approved Wave job.

• submit_quantum_job

  Reserve an exact quote and submit one bounded managed-simulator job.

• get_job_status

  Read one authorized Wave or Studio managed-simulator job.

• get_job_result

  Read one completed and already-settled product result.

• cancel_job

  Request cancellation of one authorized product job.

• get_job_artifact

  Retrieve one principal-scoped bounded Wave result artifact.

Security scan

• No findings. We scan names, descriptions and tool definitions for hidden instructions and other prompt-injection patterns.

Recent checks