RQM Jobs MCP
com.rqmtechnologies/jobsDelegate 60 specialist work products: 20 WaveEngine, 20 RQM Studio, and 20 RQM Robotics jobs.
Tools · 34
Return complete agent discovery contracts and readiness for the exact 20/20/20 RQM specialist work portfolio.
Select RQM buyer jobs from work-language requests using deterministic semantic scoring over instructions, examples, outputs, and next steps.
Describe the preserved v0/v1 surface or the dynamic v2/v3 Wave catalog.
Return one full approved public Wave capability descriptor.
Quote, settle, and submit one allowlisted WaveEngine, Studio, or Robotics buyer job using x402.
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,…
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…
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…
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…
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 ve…
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 verdi…
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 covaria…
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 resi…
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, diff…
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, determ…
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: …
Problem: Compare digital-twin output with mapped observations against caller tolerances. Input: JSON with predicted, observed, declared mapping, rules. Result: typed verdict, measured metrics, candida…
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…
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…
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 onl…
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, baselin…
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.…
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…
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…
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.... Resu…
Return a preserved v0 placeholder or a durable v1 Account Core USD quote.
Read the authenticated canonical Account Core prepaid USD balance.
Create an idempotent Stripe Checkout URL for human prepaid funding.
Reserve an exact quote and submit one bounded catalog-approved Wave job.
Reserve an exact quote and submit one bounded managed-simulator job.
Read one authorized Wave or Studio managed-simulator job.
Read one completed and already-settled product result.
Request cancellation of one authorized product job.
Retrieve one principal-scoped bounded Wave result artifact.
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How to use
Add to your Claude Desktop / Cursor / Cline MCP config:
{
"mcpServers": {
"rqm_jobs_mcp": {
"url": "https://jobs.rqmtechnologies.com/mcp",
"transport": "streamable-http"
}
}
}