lostnumber07-shearlineCAUTION
Analyst-grade US severe weather: warnings, SPC outlooks, RAP environment, MRMS, GLM lightning
Overview
From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.
[](https://pypi.org/project/shearline/) [](https://pypi.org/project/shearline/) [](https://github.com/lostnumber07/shearline/actions/workflows/ci.yml) [](https://registry.modelcontextprotocol.io/v0.1/servers?search=shearline) [](LICENSE)
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.
Tools
242dbe5963a1OBSERVED · 2026-10-10Connect
Built from this server's own package name, version and transport as found in its source — not copied from anyone's documentation, so it cannot drift against a page we do not control.
claude mcp add shearline -- uvx shearline==1.1.0
Trust audit
CAUTIONgrade B · trust 87/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | WARN |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- declared (7 observation(s))
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (11)
URL="http://127.0.0.1:${PORT}/mcp"url = f"http://127.0.0.1:{sys.argv[1] if len(sys.argv) > 1 else '8741'}/mcp"goes_glm_lcfa_sample.nc
mrms_mesh_sample.grib2.gz
mrms_rotationtrackml60min_sample.grib2.gz
rap_subset_moore.grib2
rap_subset_okc_f03.grib2
# serves at http://127.0.0.1:8741/mcp
fixtures/hrrr_subset_okc_f00.grib2
For more control, you can use the low-level server implementation directly. This gives you full access to the protocol and allows you to customize every aspect of your server, including lifecycle mana
Gates applied: no_behavioural_pass.
242dbe5963a1full audit observations/trust-audit/mcp-server/lostnumber07__shearline.json · Report an issue / request a re-scanAudit history
Every audit this server has had. A grade with a past is a grade somebody is still checking.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-10 | 242dbe5963a1 | CAUTION | B | 87 | first audit |
Questions
What is the lostnumber07-shearline MCP server?
Analyst-grade US severe weather: warnings, SPC outlooks, RAP environment, MRMS, GLM lightning
Is lostnumber07-shearline safe to connect to an agent?
With care. The audit graded it B (87/100) and found 11 things worth knowing before you trust this server, listed below with the exact line each was found on.
What credentials does lostnumber07-shearline need?
No credential environment variables were found in its source, so it appears to need none.
How does lostnumber07-shearline run?
It speaks stdio and streamable-http, so it runs as a local process your client starts. It is published on PyPI as shearline.
How current is this page?
The grade is for one exact copy of the source (242dbe5963a1), read on 2026-10-10. The repository is watched and re-audited when it changes.