Fortrip
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Description from the maker (original English)
Validated Kshana PNT simulator: orbits, GNSS, fusion, receiver trust, interference maps.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
KSHANA_MCP_IQ_DIR, KSHANA_MCP_IQ_MAX_SAMPLESYou need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"kshana": {
"command": "npx",
"args": [
"-y",
"kshana-mcp"
],
"env": {
"KSHANA_MCP_IQ_DIR": "your-value",
"KSHANA_MCP_IQ_MAX_SAMPLES": "your-value"
}
}
}
}Run this in your terminal
claude mcp add kshana --env KSHANA_MCP_IQ_DIR=your-value --env KSHANA_MCP_IQ_MAX_SAMPLES=your-value -- npx -y kshana-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"kshana": {
"command": "npx",
"args": [
"-y",
"kshana-mcp"
],
"env": {
"KSHANA_MCP_IQ_DIR": "your-value",
"KSHANA_MCP_IQ_MAX_SAMPLES": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"kshana": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"kshana-mcp"
],
"env": {
"KSHANA_MCP_IQ_DIR": "your-value",
"KSHANA_MCP_IQ_MAX_SAMPLES": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
KSHANA_MCP_IQ_DIR envKSHANA_MCP_IQ_MAX_SAMPLES envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026
The registry name was verified with the GitHub account ashfordeOU, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.39.0) reached the registry 16 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker, Node.js, Python (uv) on your computer.
In the same category: Fortrip, Bhutan Trips by Druk Asia, CarHauler247 Car Shipping Quotes
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Search hotels worldwide, compare live room rates, book and pay securely, and cancel bookings.
Bhutan trip search & booking via the Druk Asia API: festivals, itineraries, flights, bookings.
Car shipping prices between US locations from a licensed auto transport broker, with a booking link.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
kshana-mcp is a Model Context Protocol (MCP) server for Kshana, the open-source simulator for PNT (positioning, navigation and timing) resilience. It lets an AI (artificial intelligence) assistant run the real engine and read back its JSON (JavaScript Object Notation), instead of guessing the maths. It speaks over stdio (standard input and output) to any MCP-compatible client, including Cursor and JetBrains AI Assistant / Junie.
The maths Kshana is validated for is exactly where a language model guesses badly: SGP4 (Simplified General Perturbations 4) orbit propagation, reference frames of the IAU (International Astronomical Union), Allan deviations, GNSS (Global Navigation Satellite System) availability and DOP (dilution of precision), ARAIM (advanced receiver autonomous integrity monitoring) protection levels, GNSS and INS (inertial navigation system) fusion, and quantum-sensor models. Ask a question; the assistant runs a real scenario and gets figures of merit with their provenance and their VALIDATED or MODELLED label.
| Tool | What it does |
|---|---|
run_scenario | Run a scenario from a TOML (Tom's Obvious, Minimal Language) definition; returns the summary + full result JSON (JavaScript Object Notation: figures of merit, curves). Optional include_chart returns the chart as SVG (Scalable Vector Graphics). |
list_scenario_kinds | The 92 built-in scenario kinds with descriptions + required/optional fields — so the agent can construct a valid scenario. |
validate_scenario | Pre-flight check: parse the TOML and detect its kind, without running. |
list_example_scenarios | The bundled reference scenarios as JSON: each name, its kind and one sentence on what it shows. Optional kind filter. Every example runs as it stands, so this is the quickest way to a valid TOML for a kind. |
get_example_scenario | The TOML text of one bundled reference scenario, byte for byte the file under scenarios/. |
report_scenario | Run a scenario and return its report: executive summary, inputs, every figure with its unit and its VALIDATED or MODELLED label, events, the capabilities exercised and a reproducibility record. format is json (default) or html (the printable single-file page). |
animate_scenario | Run a scenario and return its time series as an animation: svg (default), html (a self-contained player) or frames (at most 120 in a reply). The first content item is a JSON summary of what was drawn; the files follow. A kind with no sampled time axis is refused with the reason. |
list_export_formats | Which interoperability formats apply to a scenario (czml, kml, geojson, stk, sigmf), the reason when one does not, and the specification each writer follows. Does not run the scenario. |
export_interop | Export a scenario as CZML (Cesium Language), KML (Keyhole Markup Language), GeoJSON, STK (Systems Tool Kit) ephemeris .e, or SigMF (Signal Metadata Format, for a spectrum scenario with an [iq] block). The first content item is a JSON index of the files (suffix, size, encoding, and the SHA-256 digest, the 256-bit Secure Hash Algorithm); the files follow, the binary SigMF sample file as base64. |
import_route | Write a GeoJSON LineString route into a scenario that flies a waypoint track (terrain-nav, terrain-slam, gravity-map, combined-altpnt) and return the new TOML. |
export_sp3 | Export an orbit scenario's constellation as SP3-c (Standard Product 3, revision c) precise ephemeris. |
export_omm | Export an orbit scenario's elements as a CCSDS (Consultative Committee for Space Data Systems) 502.0-B-2 OMM (Orbit Mean-elements Message) catalogue. |
export_oem | Export an orbit scenario's state series as CCSDS OEM (Orbit Ephemeris Message) 2.0 ephemeris — the TEME (true equator, mean equinox) position *and* velocity series flight-dynamics tools (GMAT, the General Mission Analysis Tool; Orekit; STK, the Systems Tool Kit) read; the velocity-carrying complement of the position-only export_sp3. |
export_table_csv | Run a scenario and return its reproducibility table as CSV (comma-separated values) — the byte-stable table the CLI (command-line interface) writes as .table.csv. Only realtime-frame-eop, lunar-time-budget, lunar-jamming, telecom-timing, leo-navmsg (its encode-decode analysis on a kepler16 or kepler-rac message model) and moonlight-service-volume with export_site_lat_deg + export_site_lon_deg set emit one; any other kind returns an error naming these. |
sky_geometry | Sky geometry under an azimuth-dependent skyline: from a site, a time and constellation presets, two-line element sets (tle, propagated by SGP4 to a UTC epoch) or satellites as azimuth/elevation or ECEF, the satellites visible and those hidden by the skyline, GDOP/PDOP/HDOP/VDOP/TDOP from the gnss_lib_py-checked DOP kernel, the east-north-up cofactor and covariance (one clock per system or one in common) and the horizontal error ellipse; with skyline_preset instead of request, a REPRESENTATIVE preset with its provenance and its cut every degree. MODELLED; carries the advisory; no Monte Carlo over MCP. See docs/SKYLINE.md. |
assess_receiver_log | Assess a real GNSS (global navigation satellite system) receiver log for trust. The TOML names the log's format (ubx, rinex, android, nmea or sbf) and gives its bytes inline as text or base64; the tool runs the trust monitors (carrier-to-noise density drop, loss of lock, AGC (automatic gain control), jamming indicator, position jump and, with RINEX plus broadcast navigation, RAIM (receiver autonomous integrity monitoring) and a clock-aided monitor) and returns when and why the fix stopped being trustworthy. Optional [[events]] and [compare] sections score stated events and predicted C/N0 drops against stated tolerances. A [platform] kind = "vessel" table selects the maritime monitors and adds a 0-100 trust score per epoch with the monitors that deducted (advisory; MODELLED). The log goes inline as text or base64 (at most 4 MiB). Chart and per-epoch CSV on request. See docs/RECEIVER-TRUST.md. |
assess_vessel_stream | Score a bounded NMEA 0183 excerpt (at most 2 MiB and 20,000 epochs; it must hold the calibration window) the way kshana receiver-trust live scores it: per-epoch trust state and 0-100 score with the monitors that deducted, a summary and the last $PKSHT. The bounded form of the live command: no socket is opened and nothing is written to a port; the gate, --listen and the telemetry exporters (Prometheus, OTLP, syslog) are command-line only. Advisory only; MODELLED. See docs/MARITIME-TRUST.md. |
assess_vessel_log | A vessel's NMEA 0183 log (at most 4 MiB) as a batch run, with the session TOML stating the vessel's limits: the score model and every epoch's 0-100 score with its deductions (the reply keeps counts by state and the first 200 degraded or untrusted epochs). Advisory only; MODELLED. |
jammertest_import | Read the published Jammertest test catalogue and transmission plan (NPRA/jammertest-plan, MIT) as scheduled truth (kshana jammertest import): one test area's slots become receiver-trust events with the catalogue id and year in each label. Planned slots, not recorded on-air times; no contact field of the plan is read. MODELLED. See docs/JAMMERTEST.md. |
jammertest_score | Score a receiver log against that schedule (kshana jammertest score): per test the detection latency, missed alarms and time to recover, and the false alarms outside every slot. Text logs as log, binary (ubx, sbf) as log_base64. A signed pack needs a key: command line. Advisory only; MODELLED. |
referee_location_score | Score where a monitoring network said interference came from (kshana jammertest locate-score, row B2): per report the attributed event, the geodesic error and region containment and size; per event and pooled, error percentiles, coverage per level, time to first location and time to locate; false locations per hour. Checks arithmetic, not any locator's accuracy. |
create_evidence_pack | A signed evidence pack for a window of a vessel's log (kshana receiver-trust evidence): the raw log bytes for the window, configuration, per-epoch results and reasons, a summary page, and a manifest with every SHA-256 and a hash chain, signed with Ed25519. The signing seed is never returned or logged; without one a one-time key is used, so the pack proves integrity, not identity. A technical record, not a legal opinion. See docs/EVIDENCE-PACKS.md. |
attach_evidence_timestamp | Bind an RFC 3161 timestamp token (base64 of the .tsr bytes) to a pack, in memory (kshana evidence attach-timestamp); the pack with the token must still verify. The timestamp authority's signature is not checked: use openssl ts -verify. |
verify_evidence_pack | Verify a pack (kshana evidence verify): every hash, the chain, the signature, and with the signer's public key and the full log, who signed it and that the slice came from that log. Names every failure and file. The verdict is verified (signer pinned), intact-signer-not-pinned (everything checks but no public key was given, so the signer is not established) or failed; require_timestamp fails a pack with no timestamp token. |
generate_training_nmea | Synthetic bridge NMEA 0183 for crew training from a nmea-scenario TOML (jamming, position drag-off, time spoof, replay delay) with the instructor log (kshana-nmea-training/1); deterministic per seed. Text only: nothing is synthesised at RF or IQ and nothing is transmitted; never for a vessel's live navigation systems. The reply carries the first 2000 lines. |
build_interference_map | A GNSS interference map from ADS-B or AIS position reports as CSV text (at most 4 MiB): one kshana-interference-map/v1 GeoJSON per UTC day, aggregate only (no identifiers, cells under 5 distinct aircraft or vessels withheld), with the dataset licence embedded. A degraded cell does not identify interference as the cause; not a forecast. MODELLED. See docs/INTERFERENCE-MAP.md. |
| interference_emitter_regions | Estimated emitter regions from ADS-B or AIS reports as CSV text (at most 4 MiB): regions at stated confidence levels with a centroid and an uncertainty ellipse, never a bare point; aggregate only. A region is not the position of anyone and not a finding of the cause. MODELLED. See [`docs/INTERFEREN
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