Weather MCP Server
Current weather and forecast lookup as an agent tool.
제작자가 쓴 설명(영어 원문)
Validated Kshana PNT simulator: orbits, GNSS, fusion, receiver trust, interference maps.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
KSHANA_MCP_IQ_DIR, KSHANA_MCP_IQ_MAX_SAMPLES필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"kshana": {
"command": "npx",
"args": [
"-y",
"kshana-mcp"
],
"env": {
"KSHANA_MCP_IQ_DIR": "your-value",
"KSHANA_MCP_IQ_MAX_SAMPLES": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add kshana --env KSHANA_MCP_IQ_DIR=your-value --env KSHANA_MCP_IQ_MAX_SAMPLES=your-value -- npx -y kshana-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"kshana": {
"command": "npx",
"args": [
"-y",
"kshana-mcp"
],
"env": {
"KSHANA_MCP_IQ_DIR": "your-value",
"KSHANA_MCP_IQ_MAX_SAMPLES": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"kshana": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"kshana-mcp"
],
"env": {
"KSHANA_MCP_IQ_DIR": "your-value",
"KSHANA_MCP_IQ_MAX_SAMPLES": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
KSHANA_MCP_IQ_DIR envKSHANA_MCP_IQ_MAX_SAMPLES env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 ashfordeOU 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.39.0)은 15일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Docker, Node.js, Python (uv)도 있어야 해요.
같은 카테고리에는: Weather MCP Server, Travel MCP Server, Enterprise MCP Gateway
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Current weather and forecast lookup as an agent tool.
Airbnb, hotel and TripAdvisor search as agent tools.
One MCP gateway bundling 30 data servers — finance, real estate, jobs, legal, news, sports and more.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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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