Search / io.github.pipeworx-io/jma
Jma
R0· no sign-inJMA (Japan Meteorological Agency) MCP — keyless weather forecasts, warnings,
v0.1.2 · active · repository · website · descriptor JSON · versions
Search / io.github.pipeworx-io/jma
R0· no sign-inJMA (Japan Meteorological Agency) MCP — keyless weather forecasts, warnings,
v0.1.2 · active · repository · website · descriptor JSON · versions
{
"mcpServers": {
"jma": {
"type": "http",
"url": "https://gateway.pipeworx.io/jma/mcp"
}
}
}claude mcp add --transport http jma https://gateway.pipeworx.io/jma/mcp[mcp_servers.jma]
url = "https://gateway.pipeworx.io/jma/mcp"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"jma": {
"type": "remote",
"url": "https://gateway.pipeworx.io/jma/mcp",
"enabled": true
}
}
}{
"mcpServers": {
"jma": {
"type": "http",
"url": "https://gateway.pipeworx.io/jma/mcp"
}
},
"deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=jma&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vZ2F0ZXdheS5waXBld29yeC5pby9qbWEvbWNwIn0%3D"
}{
"servers": {
"jma": {
"type": "http",
"url": "https://gateway.pipeworx.io/jma/mcp"
}
}
}{
"mcpServers": {
"jma": {
"httpUrl": "https://gateway.pipeworx.io/jma/mcp"
}
}
}extensions:
"jma":
enabled: true
name: "jma"
type: streamable_http
uri: "https://gateway.pipeworx.io/jma/mcp"
timeout: 300
Not scored: fewer than three checks apply, usually because no remote answered a credential-free probe or the server is a local package.
protocol.modernnewest supported version is 2025-03-26; 2026-07-28 not supported, older versions are deprecated until 2027-07-28protocol.statelessonly applies to 2026-07-28 serversprotocol.transportstreamable HTTPprotocol.list_ttlonly applies to 2026-07-28 serversauth.prm, auth.as_metadata, auth.cimdno remote uses OAuthauth.secret_in_urlno templated URLtools.descriptions, tools.description_length, tools.schemas, tools.annotations, tools.directory_hints, tools.token_cost, tools.api_dumptool list unknown (behind auth, not probed, or empty)stability.changes, stability.rug_pulltool list unknowndeps.known_vulns, deps.mcp_sdk_version, deps.resolvableno npm or PyPI packagejma_earthquakesremovedRecent earthquakes reported by the Japan Meteorological Agency (JMA), including magnitude, maximum seismic intensity (震度, JMA's 10-step scale: 1-4, 5 Lower, 5 Upper, 6 Lower, 6 Upper, 7), epicenter (Japanese + English where JMA publishes one), and report time. Sourced from www.jma.go.jp/bosai/quake/data/list.json, which JMA keeps as a rolling feed (typically the last few weeks of bulletins, newest first). Filter by minimum magnitude or minimum intensity to cut noise from the very small, frequent events JMA also reports.
jma_forecastremovedWeather forecast for a Japanese region from the Japan Meteorological Agency (JMA), covering a 3-day short-term outlook (weather, precipitation probability, temperature per sub-area) and a 7-day weekly outlook (weather, precipitation probability, reliability, min/max temperature with confidence range). Sourced from www.jma.go.jp/bosai/forecast/data/forecast/<office>.json. Accepts a place name in English or Japanese ("Tokyo", "Sapporo", "大阪") or a JMA office code directly — resolved the same way as jma_resolve_area. Weather text is native Japanese; an English gloss is included for JMA's fixed weatherCode set (weatherEn), derived from a static translation table, not machine-translated on the fly.
jma_resolve_arearemovedResolve a Japanese place name (English romaji or Japanese, e.g. "Tokyo", "Sapporo", "大阪") or a JMA area code to the JMA forecast OFFICE code used by jma_forecast and jma_warnings. Sourced from the Japan Meteorological Agency (JMA) area master list (www.jma.go.jp/bosai/common/const/area.json), which covers all 58 forecast offices plus every prefecture, region, city, ward and town JMA itself names in English. Use this when you need the raw office code, or just pass the place name straight into jma_forecast / jma_warnings — they resolve internally.
forgetremovedDelete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.
rememberremovedSave data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.
suggest_questionsremovedWhat can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass `topic` (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).
pipeworx_trendingremovedWhat other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.
research_rowremovedClaygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code independently verified the model's quote is a VERBATIM substring of text actually fetched; "inferred" means a value was given but the quote could not be verified; "not_established" means no source answered the field, and its value is always null — never guessed, never a blended score. Sources: "web" fetches the company's own site (entity.domain required — homepage, /about, /leadership) via fetch_url; "catalog" checks entity_profile (SEC EDGAR; resolved:false for a private company is expected, not a failure); "both" (default) tries both. max_cost (USD, default 0.02, max 0.50) scales how many pages are fetched and refuses up front if it is too small to pay for even one extraction call (floor $0.002) — never silently overspends. A row where every source comes back empty costs nothing: every field is mechanically not_established with NO model call made. For a boolean/derived field (e.g. "does this company sell to healthcare"), the quote only has to SUPPORT the value — a descriptive sentence about customers/products counts, the source need not state the answer verbatim. leadership_page_status ("fetched"|"not_found"|"not_attempted", plus leadership_note) says plainly whether a leadership/team page was actually read, so a named-person field (head_of_sales) coming back not_established is distinguishable from "this company just doesn't publish one" vs. "we never checked". model_output_empty:true means the model returned nothing usable (a transport/budget problem) — every field is not_established for THAT reason, never read as 20 individual "no" judgments. Use with a fixed question + schema across many rows for "Claygent over N companies with a hard cost cap" (composes with batch callers). For picking from a fixed label list instead of extracting open fields, use classify_row (cheaper, one model call).
archive_compareremovedWhat changed on a web page between two dates? Resolves the archived capture nearest each date (Internet Archive Wayback Machine, Common Crawl, Arquivo.pt), extracts the readable text of both, and returns a text-level diff: the segments removed and added, a similarity score, and both capture timestamps with their gaps from the requested dates. It diffs readable text, not markup, so a restyled page with the same words reads changed:false. Identical captures answer changed:false with the reason (same capture, identical content digest, or identical text), never an empty diff. A date with no capture within max_gap_days (default 30) answers status "no_capture", naming which side is missing and the nearest captures to it. Typical uses: how a privacy policy, terms of service, pricing or product page changed; whether a statement was on a page at a given time.
archive_evidenceremovedWhat did a web page say on a given date? Finds the archived capture of a URL nearest that date across the Internet Archive Wayback Machine, Common Crawl and Arquivo.pt, reads it, and returns the readable text (HTML stripped) with the capture timestamp, a link to the archived copy, and the GAP between the date asked for and the capture actually used (e.g. "Captured 1.5 day(s) before the requested date"). One call replaces the find-capture, fetch-record, parse-HTML chain. If no archive holds a capture within max_gap_days (default 30) it answers status "no_capture" and names the nearest capture before and after the date with their gaps, so a distant capture is never passed off as the page on that date. Every archive's outcome is listed in sources[]; one that timed out or errored says so with its upstream status, and if all of them failed the answer is error "archives_unavailable", not no_capture. Captures are immutable and cached by capture id; served_from says whether the text came from cache or upstream. Use archive_compare to see what changed between two dates.
Showing the latest 10. Full history: list_changes · trend: quality JSON.
Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.
+repository +namespace-matches-repo +website +reachable +uptime-99% +updated-23d-ago
Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.
| remote | auth | reachable | uptime 30d | p50 | protocol | last ok |
|---|---|---|---|---|---|---|
https://gateway.pipeworx.io/jma/mcp streamable-http | none | yes | 99% | 51 ms | 2025-03-26 | 2026-10-20 |
No tools observed. Tools appear once a credential-free probe can list them.
Schemas: list_tools.
And 1,855 more from this publisher.
{
"name": "io.github.pipeworx-io/jma",
"title": "Jma",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"remotes": [
{
"url": "https://gateway.pipeworx.io/jma/mcp",
"type": "streamable-http"
}
],
"version": "0.1.2",
"repository": {
"url": "https://github.com/pipeworx-io/mcp-jma",
"source": "github"
},
"websiteUrl": "https://pipeworx.io/packs/jma",
"description": "JMA (Japan Meteorological Agency) MCP — keyless weather forecasts, warnings,"
}