com.rqmtechnologies/jobs

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Publisher-provided title

RQM Jobs MCP

Publisher-provided description

Delegate 60 specialist work products: 20 WaveEngine, 20 RQM Studio, and 20 RQM Robotics jobs.

Summary by lookupd

Lets agents discover, quote, purchase, and track specialist quantum and robotics analysis jobs, plus robotics validation and calibration…

Install

Claude Code, remote (streamable-http)

claude mcp add --transport http jobs https://jobs.rqmtechnologies.com/mcp

Codex, remote (streamable-http)

codex mcp add jobs --url https://jobs.rqmtechnologies.com/mcp

Cursor, remote (streamable-http) → .cursor/mcp.json

{
  "mcpServers": {
    "jobs": {
      "url": "https://jobs.rqmtechnologies.com/mcp"
    }
  }
}

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (showing 30 of 39)

Publisher-provided text

• 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,
• 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 sel
• 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 followi
• 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
• 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
• 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 le
• 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, rul
• 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, r
• 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.
• 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, observatio
• 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 traj
• 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, rule
• 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. Resu
• 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:
• 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-
• 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
• 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:
• 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 e
• 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: ty
• 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
• 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,
• 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: eigenv
• 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 radi
• 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 re
• 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, stiff

Details

• Version: 1.6.0
• Transports: streamable-http
• Uptime (7 days): 100%
• Median latency: 1277 ms
• First indexed: 2026-11-01T08:57:36.565Z
• Last seen in registry: 2026-11-01T08:57:36.601Z
• Repository: https://github.com/RQM-Technologies-dev/RQM-Jobs-MCP
• Website: https://www.rqmtechnologies.com/docs

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