MCP server

RQM WaveEngine Jobs

com.rqmtechnologies/waveengine

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Delegate 20 typed, evidence-backed WaveEngine signal work products with fixed-request x402.

Website Source

At a glance

Type

MCP server

Publisher

rqmtechnologies.com (verified by the MCP Registry)

Status

Working at last check

Tools

34

Token cost

About 9,934 tokens per request

Sets up in

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

Last checked

25 Oct 2026, 20:29 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 waveengine https://jobs.rqmtechnologies.com/mcp/waveengine

Claude Desktop

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

Codex (config.toml)

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

Gemini CLI

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

Cursor

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

VS Code

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

Antigravity

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

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":"waveengine","server_url":"https://jobs.rqmtechnologies.com/mcp/waveengine","require_approval":"always"}

Grok (xAI API tools)

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

Tools

• estimate_wave_job ~248 tokens
  Validate a bounded request against the live catalog and return a non-binding price and duration estimate without authentication.
• get_wave_capability ~96 tokens
  Return one full approved public Wave capability descriptor.
• get_wave_example ~108 tokens
  Return one realistic illustrative request/result shape, artifact list, expected duration, and price guard.
• get_wave_job_artifact ~156 tokens
  Retrieve one principal-scoped bounded Wave result artifact.
• get_wave_job_result ~281 tokens
  Read one completed and already-settled product result.
• get_wave_job_status ~282 tokens
  Read one authorized Wave or Studio managed-simulator job.
• get_wave_receipt ~176 tokens
  Retrieve the durable Account Core receipt for one settled WaveEngine reservation.
• list_wave_capabilities ~173 tokens
  Describe the preserved v0/v1 surface or the dynamic v2/v3 Wave catalog.
• run_wave_example ~112 tokens
  Execute the catalog-owned bounded example through the real typed WaveEngine adapter without accepting arbitrary input.
• run_wave_job ~472 tokens
  Pay anonymously with x402 by default, or explicitly use an authenticated Account Core balance, then submit one idempotent WaveEngine job.
• search_wave_capabilities ~265 tokens
  Deterministically rank executable WaveEngine capabilities for a natural-language task and bounded filters.
• wave_apply_verified_phase_correction_v1 ~339 tokens
  Problem: Apply this bounded phase correction and verify the supplied preservation assertions. Input: JSON with sample rate hz, channels, angle radians, assertions. Result: corrected capture and preservation checks. Limits: Bounded signal processing only; 2 channels; 1024 samples/channel.
• wave_compare_pipeline_responses_v1 ~345 tokens
  Problem: Compare these two supported Wave pipelines on the supplied fixture and caller tolerances. Input: JSON with left pipeline, right pipeline, fixture, maximum rmse, maximum absolute.... Result: response differences and tolerance checks. Limits: Bounded signal processing only; 8 channels; 4096 s
• wave_compare_waveform_captures_v1 ~345 tokens
  Problem: Compare these two bounded waveforms against the supplied alignment and numeric rules. Input: JSON with sample rate hz, channels, reference channel id, candidate channel id, rules. Result: waveform differences and caller-rule results. Limits: Bounded signal processing only; 2 channels; 1024
• wave_compile_curated_processing_recipe_v1 ~336 tokens
  Problem: Compile this curated processing recipe and return its validated pipeline and execution trace. Input: JSON with fixture, maximum round trip rmse. Result: validated pipeline and execution trace. Limits: Bounded signal processing only; 8 channels; 4096 samples/channel.
• wave_convert_capture_to_spectrum_v1 ~339 tokens
  Problem: Convert this bounded complex capture into a checksummed spectral artifact with declared normalization. Input: JSON with sample rate hz, channel, normalization. Result: spectrum with normalization and checksums. Limits: Bounded signal processing only; 8 channels; 4096 samples/channel.
• wave_diagnose_multichannel_capture_v1 ~342 tokens
  Problem: Diagnose this coordinated complex capture for bounded Wave-Intelligence degradation findings without inferring a physical cause. Input: JSON with sample rate hz, channels. Result: bounded capture findings and artifacts. Limits: Bounded signal processing only; 8 channels; 1024 samples/channe
• wave_equalize_pilot_capture_v1 ~339 tokens
  Problem: Fit a bounded quaternion NLMS equalizer to this received and desired pilot capture. Input: JSON with input channels, output channels, received, desired, pilot mask. Result: fitted equalizer and pilot-fit evidence. Limits: Bounded signal processing only; 4 channels; 1024 samples/channel.
• wave_extract_wave_features_v1 ~334 tokens
  Problem: Convert this coordinated complex capture into the deterministic versioned Wave-Intelligence feature vector. Input: JSON with sample rate hz, channels. Result: versioned feature vector and artifacts. Limits: Bounded signal processing only; 8 channels; 1024 samples/channel.
• wave_fit_coupled_channel_model_v1 ~338 tokens
  Problem: Fit a bounded structured quaternion ridge model to these coupled channel features and targets. Input: JSON with feature count, output count, features, targets. Result: fitted channel model and fit evidence. Limits: Bounded signal processing only; 16 channels; 512 samples/channel.
• wave_gate_signal_capture_v1 ~345 tokens
  Problem: Accept or reject this bounded signal capture against the caller-supplied metric rules and return every measurement and violation. Input: JSON with sample rate hz, channels, rules. Result: measurements, violations and checksummed artifacts. Limits: Bounded signal processing only; 8 channels;
• wave_generate_validated_signal_fixture_v1 ~344 tokens
  Problem: Generate this bounded sine or safe-formula signal fixture and return reproducibility, measurement, checksum, and validation evidence. Input: JSON with fixture. Result: signal fixture, checksums and validation evidence. Limits: Bounded signal processing only; 8 channels; 16384 samples/channe
• wave_measure_phase_drift_v1 ~347 tokens
  Problem: Measure phase drift in this bounded complex observation against the supplied reference and tolerances. Input: JSON with reference, observation, maximum absolute drift radians, maximum rms.... Result: phase drift measurements and tolerance checks. Limits: Bounded signal processing only; 8 ch
• wave_optimize_processing_pipeline_v1 ~351 tokens
  Problem: Optimize this supported Wave pipeline against the supplied operation-count objective and equivalence rule. Input: JSON with operations, fixture, objective, maximum operations, maximum equivalence.... Result: candidate pipeline and equivalence checks. Limits: Bounded signal processing only;
• wave_reconstruct_bounded_capture_v1 ~352 tokens
  Problem: Reconstruct this bounded capture under the supplied transfer assumption and verify it against the reference rules. Input: JSON with observation, reference, assumed transfer, maximum rmse, maximum.... Result: reconstructed capture and reference-rule checks. Limits: Bounded signal processing
• wave_reconstruct_time_domain_signal_v1 ~346 tokens
  Problem: Convert these bounded frequency bins into time-domain samples and verify the caller's round-trip rule. Input: JSON with sample rate hz, frequency bins, normalization, rules. Result: time-domain samples and round-trip verification. Limits: Bounded signal processing only; 8 channels; 4096 sam
• wave_rotate_and_validate_two_channel_frame_v1 ~336 tokens
  Problem: Rotate these two coordinated complex channels with the supplied rotor and validate caller invariants. Input: JSON with channels, rotor, rules. Result: rotated channels and invariant checks. Limits: Bounded signal processing only; 8 channels; 4096 samples/channel.
• wave_transport_polarization_frame_v1 ~338 tokens
  Problem: Transform these Jones vectors or channel operators between the explicitly named SU(2) frames and verify invariants. Input: JSON with mode, rotor. Result: transformed vectors/operators and invariant checks. Limits: Bounded signal processing only; 4 channels; 1024 samples/channel.
• wave_validate_reconstruction_quality_v1 ~332 tokens
  Problem: Compare this reconstruction with the supplied reference and acceptance rules. Input: JSON with reference, reconstruction, rules. Result: reconstruction differences and rule results. Limits: Bounded signal processing only; 8 channels; 4096 samples/channel.
• wave_validate_spectral_criteria_v1 ~336 tokens
  Problem: Accept or reject this bounded capture against the caller's supplied spectral criteria. Input: JSON with sample rate hz, channel, normalization, rules. Result: spectral metrics and caller-rule verdict. Limits: Bounded signal processing only; 8 channels; 4096 samples/channel.
• wave_verify_wave_pipeline_v1 ~348 tokens
  Problem: Execute and verify this bounded Wave IR pipeline against the required representation, shape, and optional round-trip assertions. Input: JSON with sample rate hz, channels, operators, assertions. Result: execution result and shape/round-trip checks. Limits: Bounded signal processing only; 2

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