Analyst-grade US severe weather: warnings with IBW tags, SPC outlooks, RAP environments, MRMS, LSRs
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The severe-weather analyst your agent doesn't have. SHEARLINE is a free, MIT-licensed MCP server that gives AI agents analyst-grade US severe-weather tools: live warning polygons with Impact-Based Warning tags, SPC convective outlooks, RAP-derived point environments and forecast trends (CAPE/shear/SRH/STP computed with MetPy), MRMS radar-derived hail and rotation products, GOES lightning, ground-truth storm reports (real-time and historical), and a composite threat brief that synthesizes all of it. A dozen weather MCPs already wrap the basic forecast API; SHEARLINE deliberately skips everything they do and ships only what requires radar meteorology to expose correctly.
Informational only. Not a substitute for official NWS warnings. Every tool repeats this, because it matters: when weather threatens, follow official warnings from weather.gov and local authorities.
| Tool | What it returns |
|---|---|
get_active_warnings(lat, lon, radius_km=40) | Active tornado/severe-thunderstorm/flash-flood warning polygons with IBW tags (max hail size, max gust, tornado detection/damage threat), parsed storm motion, expirations, and whether the exact point is inside a polygon. Watches listed separately. |
get_spc_outlook(lat, lon, day=1) | SPC categorical risk (TSTMβHIGH) at the point plus tornado/hail/wind probabilities and significant-severe flags, days 1β3, with interpretation calibrated to the category. |
get_point_environment(lat, lon) | Latest RAP 13-km analysis profile computed with MetPy: MLCAPE/MUCAPE/CINs, LCL, 0β1/0β6 km shear, 0β1/0β3 km SRH, Bunkers motion, effective inflow layer, effective SRH/shear, SCP, and significant-tornado parameter β interpreted like an analyst (pulse vs. cool-season high-shear vs. classic supercell parameter space). |
get_environment_trend(lat, lon) | The anticipatory view: a short RAP forecast series (f00/f01/f03/f06, one consistent cycle) of MLCAPE, 0β6 km shear, 0β1 km SRH, SCP and STP, with an interpretation of the trajectory (intensifying / stabilizing / steady) β for "is this getting worse" rather than "what is it now." |
get_mrms_severe(lat, lon, radius_km=40) | MRMS maxima within radius: 60-min MESH (hail, inches and mm), low-level and mid-level rotation tracks (azimuthal shear), VIL, composite reflectivity β each with valid time and distance/bearing of the max. |
get_storm_reports(lat, lon, radius_km=80, hours=6) | Normalized Local Storm Reports: type, magnitude with units, time, location, distance/bearing, remarks. |
get_lightning(lat, lon, radius_km=40, minutes=15) | GOES-East GLM total-lightning activity in the recent window: flash count and rate, nearest strike (distance/bearing/time), and a tiered outdoor-safety interpretation (overhead / within-striking-distance / in-the-area). |
get_historical_storm_reports(lat, lon, date, radius_km=80) | What hail/wind/tornado hit a point on a specific past date (YYYY-MM-DD, UTC) β normalized reports with magnitude+units and distance/bearing, for the insurance / ag / forensic use case. Coverage from ~2005; preliminary LSRs, not the final NCEI record. |
get_threat_brief(lat, lon) | The showpiece: runs everything above concurrently and synthesizes a threat level (none/marginal/elevated/significant/extreme) with stated logic, hazards ranked, environment summary, nearest storm signature, and a recommended attention window. |
get_radar_snapshot(lat, lon) | Nearest WSR-88D's latest Level 2 volume metadata: VCP (scan strategy), max reflectivity with range/azimuth, coarse echo-top estimate. |
Every tool returns structured JSON with data (numeric fields, units stated), interpretation (plain-language analyst sentences), degraded (which upstream sources failed, if any β partial data instead of errors), the safety disclaimer, and a schema_version β the field contract is semver-stable (see ARCHITECTURE), so integrators can depend on it.
Real output from 2026-06-10, point inside an active tornado warning in northern Missouri:
And the same tool for a quiet coastal Maine point reads as confidently quiet β not as an error: "threat_level": "none" with the environment numbers shown so the agent can see why it's quiet.
Requires Python 3.12+ and uv. No API keys β every data source is public and anonymous. uvx downloads and runs the published package in one step; nothing is installed permanently.
Claude Code:
Claude Desktop (claude_desktop_config.json):
Streamable HTTP (for remote/agent-platform use):
On macOS you can also double-click scripts/launch.command to start the HTTP server in a Terminal window (honours SHEARLINE_PORT).
The HTTP transport is built to be hosted: it emits one structured JSON log line
per tool call (tool, coarse 1Β° lat/lon bucket, latency, degraded list, cache
hit/miss) and applies a per-client token-bucket rate limit, returning 429 with
Retry-After when exceeded. Both are HTTP-only β stdio behaviour is
unchanged. Configure via environment variables:
| Env var | Default | Effect |
|---|---|---|
SHEARLINE_RATE_RPM | 60 | sustained requests/minute/client (0 disables the limit) |
SHEARLINE_RATE_BURST | 30 | token-bucket capacity (max burst) |
SHEARLINE_HTTP_LOG | 1 | set 0 to silence per-request logging |
SHEARLINE_LOG_LEVEL | INFO | log level for the shearline.http logger |
SHEARLINE_UPSTREAM_CONCURRENCY | 8 | max concurrent upstream fetches (politeness toward NOAA) |
To run the latest unreleased main instead of the PyPI release, swap shearline for --from git+https://github.com/lostnumber07/shearline shearline.
A forecast API tells you it might rain. None of the questions that matter on a severe weather day β is this storm rotating, how big is the hail, is the environment loaded for tornadoes, am I inside the polygon β are answerable from a forecast endpoint. They require the warning's IBW tags, radar-derived products, and a real sounding:
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