MCP server

RQM Jobs MCP

com.rqmtechnologies/jobs

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Website Source

At a glance

Type

MCP server

Publisher

rqmtechnologies.com (verified by the MCP Registry)

Status

Working at last check

Tools

39

Token cost

About 15,000 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

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

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.jobs]
url = "https://jobs.rqmtechnologies.com/mcp"

Gemini CLI

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

Cursor

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

VS Code

{"servers":{"jobs":{"type":"http","url":"https://jobs.rqmtechnologies.com/mcp"}}}

Antigravity

agy mcp add jobs https://jobs.rqmtechnologies.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"jobs","server_url":"https://jobs.rqmtechnologies.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"jobs","server_url":"https://jobs.rqmtechnologies.com/mcp"}

Tools

• cancel_job ~469 tokens
  Request cancellation of one authorized product job.
• create_funding_session ~165 tokens
  Create an idempotent Stripe Checkout URL for human prepaid funding.
• describe_quantum_capabilities ~253 tokens
  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; unavailable chemist
• get_account_balance ~103 tokens
  Read the authenticated canonical Account Core prepaid USD balance.
• get_account_job ~292 tokens
  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 their limitations. If t
• get_capability ~453 tokens
  Return one full approved public Wave capability descriptor.
• get_job_artifact ~154 tokens
  Retrieve one principal-scoped bounded Wave result artifact.
• get_job_result ~363 tokens
  Read one completed and already-settled product result.
• get_job_status ~364 tokens
  Read one authorized Wave or Studio managed-simulator job.
• list_account_jobs ~299 tokens
  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 recent history, or pass
• list_buyer_jobs ~172 tokens
  Return complete agent discovery contracts and readiness for the exact 20/20/20 RQM specialist work portfolio.
• list_capabilities ~384 tokens
  Describe the preserved v0/v1 surface or the dynamic v2/v3 Wave catalog.
• quote_job ~1286 tokens
  Return a preserved v0 placeholder or a durable v1 Account Core USD quote.
• robotics_analyze_force_disturbance_response_v1 ~350 tokens
  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 only; 65536 request
• robotics_assess_calibration_quality_v1 ~349 tokens
  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 evidence only; 65536 reques
• robotics_check_collision_constraints_v1 ~348 tokens
  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 only; 65536 request b
• robotics_compare_controller_responses_v1 ~339 tokens
  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 execution.
• robotics_compare_digital_twin_observations_v1 ~343 tokens
  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; 5 s execution.
• robotics_compare_planned_observed_trajectories_v1 ~335 tokens
  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_state_estimators_v1 ~344 tokens
  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 request bytes; 5 s exe
• robotics_compute_actuator_alignment_correction_v1 ~346 tokens
  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 request bytes; 5 s executi
• robotics_diagnose_trajectory_instability_v1 ~349 tokens
  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 only; 65536 request b
• robotics_estimate_fused_state_v1 ~343 tokens
  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 request bytes; 5 s ex
• robotics_frame_convention_validation_v1 ~362 tokens
  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, normalized evidence. Limit
• robotics_normalize_sensor_frames_v1 ~348 tokens
  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 only; 65536 request
• robotics_optimize_disturbance_rejection_v1 ~358 tokens
  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. Limits: Software/mod
• robotics_optimize_trajectory_to_constraints_v1 ~343 tokens
  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; 5 s execution.
• robotics_reconstruct_smoothed_trajectory_v1 ~337 tokens
  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_replay_workcell_trace_v1 ~328 tokens
  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_tune_controller_to_objectives_v1 ~347 tokens
  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; 65536 request bytes; 5
• robotics_validate_closed_loop_stability_v1 ~336 tokens
  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_validate_kinematic_dynamic_limits_v1 ~341 tokens
  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 execution.
• robotics_validate_trajectory_timing_v1 ~344 tokens
  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 request bytes; 5 s exec
• run_account_job ~758 tokens
  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_id; validate the use
• run_buyer_job ~340 tokens
  Quote, settle, and submit one allowlisted WaveEngine, Studio, or Robotics buyer job using x402.
• search_buyer_jobs ~221 tokens
  Select RQM buyer jobs from work-language requests using deterministic semantic scoring over instructions, examples, outputs, and next steps.
• settle_buyer_job ~542 tokens
  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.
• submit_quantum_job ~840 tokens
  Reserve an exact quote and submit one bounded managed-simulator job.
• submit_wave_job ~652 tokens
  Reserve an exact quote and submit one bounded catalog-approved Wave job.

Browse

• Stripe tools
• Website monitoring
• Payments
• Hiring and jobs

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