Tools Reference¶

All 34 RFlect MCP tools, organized by category. Full signatures and return shapes.

Import (6)¶

Tool	Purpose
`import_antenna_file(file_path, scan_type)`	Single measurement file (auto-detects scan type from filename)
`import_antenna_folder(folder_path, pattern, scan_type)`	Every file in folder matching glob
`import_passive_pair(hpol_file, vpol_file, cable_loss, name)`	HPOL+VPOL → full passive calc pipeline
`import_active_processed(file_path, name)`	Single TRP file with full active calc pipeline
`list_loaded_data()`	Currently loaded measurements
`clear_data()`	Drop all loaded measurements

Analysis (5)¶

Tool	Purpose
`list_frequencies()`	Available frequencies across loaded data
`analyze_pattern(frequency, polarization)`	HPBW, F/B ratio, nulls, sidelobes
`get_gain_statistics(frequency)`	Min / max / spherical avg gain
`compare_polarizations(frequency)`	AR / tilt / XPD / sense
`get_all_analysis(frequency)`	Combined pattern + gain + polarization

Reports (3)¶

Tool	Purpose
`generate_report(output_path, options, title, metadata)`	DOCX with plots, tables, AI summary
`preview_report(options)`	What the report would contain — no file written
`get_report_options()`	All filtering / customization options

Bulk (5)¶

Tool	Purpose
`list_measurement_files(folder_path)`	Scan folder, categorize HPOL/VPOL/TRP/VSWR
`bulk_process_passive(folder_path, frequencies, cable_loss, save_path, datasheet_plots)`	Batch HPOL/VPOL pairs
`bulk_process_active(folder_path, save_path, interpolate)`	Batch TRP files
`validate_file_pair(hpol_path, vpol_path)`	Are these two files a valid pair?
`convert_to_cst(hpol, vpol, vswr, frequency, cable_loss, output_path)`	Export CST `.ffs`

UWB (3)¶

Tool	Purpose
`calculate_sff_from_files(file_paths, pulse_type, min_freq_ghz, max_freq_ghz)`	SFF per angle from a list of files
`analyze_uwb_channel(file_path, distance_m, pulse_type)`	Full UWB analysis from one file
`get_impedance_bandwidth(file_path, threshold_dB)`	S11 bandwidth metrics

Cal Drift (8)¶

Tool	Purpose
`cal_drift_ingest(directory)`	Walk a directory of `TRP Cal *.txt` and record each
`cal_drift_list_runs(antenna, band)`	List recorded runs, optionally filtered
`cal_drift_compare(baseline_run_id, current_run_id, max_delta_rows)`	Per-frequency ΔdB + consistency
`cal_drift_report(baseline_run_id, current_run_id, output_path, format)`	Export markdown / pdf / png
`cal_drift_history_dir()`	Current history directory
`cal_drift_set_history_dir(directory)`	Persist a new history directory
`cal_drift_set_setup_group(run_id, setup_group)`	Tag a run's methodology epoch
`cal_drift_set_notes(run_id, notes)`	Free-text operator notes

Orchestration (1)¶

Tool	Purpose
`process_folder(folder_path, intent, report, freqs, report_path)`	Scan folder, pick + run the right workflow

Returns:

{
  "intent_used":        "passive" | "active" | "cal_drift" | "uwb" | None,
  "files_scanned":      int,
  "files_processed":    int,
  "frequencies_loaded": list[float],
  "warnings":           list[str],     # never raises; failures here
  "report_path":        str | None,
  "extra":              dict           # intent-specific (uwb results, cal_drift run_ids, …)
}

See Recipes for usage patterns.

Validation (1)¶

Tool	Purpose
`analyze_iperf_angle_sweep(session_dir, reference_session_dir, out_dir, mean_threshold_mbps, worst_threshold_mbps)`	Per-angle throughput delta of an installed antenna vs a reference, across azimuth

Compares two bench iperf sessions — an installed-antenna session and a matched reference-antenna session recorded at the same azimuth angles. For each (channel, mode) cell it computes the per-angle deltas (installed − reference) and a roll-up: mean, median, worst-angle, best-angle, spread, and p10/p90. It writes summary.csv, summary.json, a polar PNG per cell, and a markdown report.md with a configurable adequacy verdict.

Returns:

{
  "summary_csv":  str | None,
  "summary_json": str | None,
  "report_md":    str | None,
  "polar_pngs":   list[str],
  "n_cells":      int,
  "warnings":     list[str],     # never raises; failures here
}

Reads only the documented bench session.json shape (wifi_only runs carrying angle_deg and aggregate.overall_mbps); it has no dependency on any specific bench harness. See Recipes for usage patterns.

RF Analysis (6)¶

Deterministic wrappers over plot_antenna math (no LLM, no network). Each returns a structured dict and never raises; failures appear in a warnings list.

Tool	Purpose
`compare_antennas(measurement_names, reference, out_csv)`	Cross-measurement overlay: per-frequency peak gain/TRP, deltas vs a reference, best-per-frequency, best-overall, optional CSV
`analyze_s11(freq_hz, s11_db, threshold_db, include_vswr_curve)`	Return loss / impedance bandwidth / VSWR / resonance from an S11 sweep
`analyze_group_delay(freq_hz, phase_deg, band_start_hz, band_stop_hz)`	Group delay + in-band flatness from a transmission-phase sweep (phase only)
`estimate_link_budget(tx_power_dbm, rx_sensitivity_dbm, tx_gain_dbi, rx_gain_dbi, freq_mhz, ...)`	Max range + link margin via Friis / log-distance / ITU-indoor; optional Rayleigh/Rician fade margin and de-rated reliable range
`analyze_mimo_diversity(ecc, snr_db, snr_sweep_db, fading, rician_k)`	ECC → Vaughan-Andersen diversity gain, 2×2 capacity, isolation rating, optional capacity-vs-SNR curve
`generate_active_cal(power_measurement_file, gain_standard_file, hpol_file, vpol_file, freq_list, cable_loss)`	Generate an active chamber cal file + summary; auto-records into cal-drift history

compare_antennas operates on the loaded-measurement store (import first). The others take agent-supplied arrays/scalars — pair them with measured values (e.g. use the peak gain from get_gain_statistics as tx_gain_dbi, or an ECC from measured patterns for analyze_mimo_diversity).

Misc (3)¶

Tool	Purpose
`get_measurement_details(measurement_name)`	Inspect one loaded measurement
`batch_analyze_frequencies()`	Re-run analysis across all loaded frequencies
`rflect://help`	Help resource — server prints categorized tool list

Source of truth¶

Registration entry points:

rflect-mcp/tools/import_tools.py — register_import_tools(mcp)
rflect-mcp/tools/analysis_tools.py — register_analysis_tools(mcp)
rflect-mcp/tools/report_tools.py — register_report_tools(mcp)
rflect-mcp/tools/bulk_tools.py — register_bulk_tools(mcp)
rflect-mcp/tools/uwb_tools.py — register_uwb_tools(mcp)
rflect-mcp/tools/cal_drift_tools.py — register_cal_drift_tools(mcp)
rflect-mcp/tools/orchestration.py — register_orchestration_tools(mcp)

All registered in rflect-mcp/server.py.