World Monitor
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
作者による説明(英語の原文)
Read-only MCP server for wafergraph.com's semiconductor & AI supply-chain data: 30 tools, no auth.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://wafergraph-mcp.jwpalm99.workers.dev/mcpターミナルでこれを実行します
claude mcp add --transport http wafergraph https://wafergraph-mcp.jwpalm99.workers.dev/mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"wafergraph": {
"url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"wafergraph": {
"type": "http",
"url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ChatGPTがつなげるのは、インターネット上のサーバーだけです:
https://wafergraph-mcp.jwpalm99.workers.dev/mcpメニューの名前は、プランや時期によって少し違うことがあります。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
このサーバーのつなぎ方と、各アプリの公式ドキュメントに基づきます。2026年11月10日に確認。
インターネット経由でつなげるアプリ
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
ツールの名前と説明は、サーバーが2026年11月10日に返したそのままの内容です。書いたのは作者で、私たちではありません。プレーンテキストとして表示しています。
search_companiesSearch wafergraph's semiconductor & AI supply-chain company dataset (615 companies across 12 segments) by name/one_liner substring and/or segment and/or country. Returns a compact list capped at 25 with a total match count. Use get_segments first if you don't know valid segment i
get_companyFull allowed profile for one company (by id or exact name) plus its supplier/customer supply-chain edges. Includes key_products (short list of named products/lines). Fields are deliberately limited to established/trust-checked data (see README field-discipline note).
get_segmentsThe wafergraph taxonomy: 12 top-level supply-chain segments (materials through ai_datacenter) and their subsegments, each with a live company count, plus the market_position enum. Use this to discover valid `segment` values for search_companies/get_deals. Segment definitions are
get_supply_chainWalk the supplier/customer graph from one focal company, up to 2 tiers up (suppliers), down (customers), or both. Mirrors the chain view on wafergraph.com's Explorer. Returns companies grouped by tier plus the edges between them.
get_dealsSearch wafergraph's semiconductor & AI supply-chain M&A corpus (74 acquisitions/mergers, including notable terminated attempts) by title/summary substring and/or segment. Returns a compact list capped at 30 with a total match count.
compare_companiesSide-by-side comparison of 2-6 companies on the same fields, plus their shared and unique supply-chain counterparties. Cheaper and more aligned than several get_company calls when the question is comparative.
get_country_exposureGeographic concentration of the supply chain: which countries host the companies in a given segment (or across all 12 segments), ranked by company count. Answers 'how concentrated in Taiwan is advanced lithography' style questions. Country is recorded for all 615 companies.
find_chokepointsRank supply-chain chokepoints: companies many others depend on, weighted by how concentrated their market position is. A chokepoint here means high downstream dependency plus monopoly/leader position, i.e. few substitutes. Scoring is a transparent heuristic over the public datase
analyze_portfolio_exposureGiven a list of tickers or company ids, report that basket's aggregate exposure across supply-chain segments and countries, and flag where holdings share the same upstream suppliers (correlated single points of failure). Informational supply-chain analysis over public data, not i
filter_companiesStructured multi-criteria screen over all 615 companies: exact segment/subsegment/country/market_position/public filters plus a market-cap range, sortable and paginated. Use this instead of search_companies when the question is a precise filter ('leader-position analog companies
list_subsegmentsEvery subsegment across wafergraph's 12-segment taxonomy, each with its live company count and parent segment id/name, optionally filtered to one segment. Use this (or get_segments) to discover valid `subsegment` values before calling get_subsegment or filter_companies. Segment/s
get_subsegmentAll companies in one segment+subsegment pair, as compact refs sorted by market cap descending, plus a market_position breakdown and a country breakdown computed over the FULL matching set (not just the returned page). Use list_subsegments first if you don't know valid segment/sub
find_similar_companiesNearest structural neighbours to one focal company, ranked by a transparent Jaccard-similarity score — not a market or competitive judgment. Use search_companies or resolve_ticker first if you only have a ticker or an approximate name, then pass the resolved id here.
rank_by_market_capTop N companies by market cap, optionally restricted to a segment/country/market_position, with the priced-coverage ratio for that scope attached — about 28% of companies dataset-wide have no market_cap_usd_b on file, so a plain top-N list without the coverage number would look m
resolve_tickerBatch-resolve up to 25 strings — tickers, company names, or ids, in any mix — to canonical company refs. Call this FIRST whenever you have raw user input (a ticker list, pasted names) and need valid ids before calling other tools; unresolved entries come back with up to 3 suggest
list_countriesEvery country in wafergraph's semiconductor & AI supply-chain dataset (29 countries across 615 companies) with company count, which segments are present there (with counts), public/private split, and priced market-cap totals. Sorted by company count descending. Optional segment f
get_country_profileDeep profile of one country's presence in wafergraph's semiconductor & AI supply-chain dataset: company count, segment breakdown, market-position breakdown, top companies by market cap, notable monopoly/leader companies, and inbound/outbound supplier-relationship edge counts acro
compare_countriesSide-by-side comparison of 2-5 countries: aligned rows for company count, segment mix, market-position mix, and priced market cap, plus which segments each country is uniquely present in or dominant in, and which segments they all share. country is the company's HEADQUARTERS coun
get_segment_leadersWho runs a given layer of the semiconductor & AI supply chain: the companies at monopoly/leader market position in one taxonomy segment (or all 12 if none given), with country and market cap, plus a count of how many companies sit at each position (monopoly/leader/major/challenge
get_upstream_concentrationFor one focal company: break its suppliers down by headquarters country and by segment, report an HHI concentration index (0 = spread evenly, 1 = fully concentrated in one bucket) for each dimension, and name the single most concentrated one. Always reports supplier_edge_coverage
find_paths_betweenEvery documented supply path between two companies, following supplier->customer edges (e.g. 'how does NVIDIA actually depend on Shin-Etsu'). Searches up to max_depth hops in one or both directions and returns each path as an ordered list of companies, shortest first. Capped for
simulate_disruptionRemove one company, every company in one country, or every company in one segment from the documented supply graph and report the blast radius: which companies lose a documented supplier, how many alternative suppliers they retain in the same subsegment, and which are left with z
find_single_source_dependenciesScreen for (customer, subsegment) pairs where the customer has exactly ONE documented supplier in that subsegment — the highest-value documented-concentration risk screen in the dataset. Optionally scoped to customers in one segment or country. Ranked by the sole supplier's downs
rank_by_connectivityRank companies by documented supply-chain degree: customer count (downstream reach), supplier count (upstream dependence), or total. CRITICAL: degree measures how well a relationship is DOCUMENTED in this curated dataset, not how critical the company actually is — a well-covered
find_common_suppliersThe shared-upstream question over a set of companies: given 2-15 company ids/tickers, or a segment id (uses every company in that segment), rank suppliers by how many of the input companies they documentedly serve (e.g. 'serves 9 of 12'), with each supplier's market position and
get_dealFull record for one M&A deal by id: title, type, value, announced date, status, all parties with their resolved company refs where a dataset id exists (and the raw party name where it does not), summary, sources, and the per-deal confidence flag. Use get_deals or find_deals_by_co
find_deals_by_companyEvery M&A deal a company took part in, split by role (as acquirer, as target, or other). Matches by dataset id first, then falls back to case-insensitive name matching — necessary because a deal's target is frequently not itself a company in this dataset and carries a null id (e.
get_ma_activity_summaryAggregate view of the full 74-deal M&A corpus: counts by year (from announced date), by deal type, and by status; total and median disclosed value; and the largest deals by value. Value figures are computed only over the subset of deals with a disclosed value_usd and are never ex
find_consolidation_hotspotsRanks taxonomy segments by M&A activity by mapping each deal's parties onto their companies' segments (matching by id, then falling back to case-insensitive name), then aggregating deal count and disclosed value per segment. Deals whose parties cannot be resolved to any dataset c
get_dataset_statsThe honesty tool: what this dataset actually contains and where it is thin. Live-computed per-field coverage for companies and deals, last_verified staleness distribution, supply-chain edge coverage, data source mode, and a plain-words list of known limitations. Call this before
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月11日にチェック
レジストリ名はドメイン wafergraph.com で確認済みです(レジストリがドメインの所有を確認しています)
コードの最終更新:2 か月前
このリポジトリはまだGitHubから読み取っていません
637ミリ秒で応答(HTTP 200)
サインイン不要
30件のツールの説明を読み、AIへの隠れた指示は見つかりませんでした
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック4項目のうち4項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。
GitHubリポジトリの最終更新は2 か月前、最新バージョン(1.2.0)がレジストリに届いたのは3 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
同じカテゴリには:World Monitor, Claude Flow, Tldraw
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:↓ 週あたりのダウンロードi★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
A remote MCP server exposing wafergraph.com's semiconductor & AI supply-chain dataset — 565 companies across 12 segments, the supplier/customer graph, and a 74-deal M&A corpus — as 30 read-only tools any MCP-speaking AI agent can call directly.
No auth, no cost, read-only. Streamable HTTP transport at /mcp. Human landing page at /.
Live: https://mcp.wafergraph.com
| Tool | Purpose |
|---|---|
search_companies({query?, segment?, country?}) | Name/description search with segment & country filters. Compact list, capped at 25, with a total match count. |
get_company({id}) | Full allowed profile for one company (by id or name) plus its supplier/customer edges. |
get_segments() | The 12-segment taxonomy (+ subsegments, market_position enum) with live company counts. |
get_supply_chain({id, direction, depth}) | Walk the supplier/customer graph from a focal company up to 2 tiers up ("up"), down ("down"), or "both". |
get_deals({query?, segment?}) | Search the M&A deal corpus. Compact list, capped at 30, with a total match count. |
compare_companies({ids}) | Side-by-side comparison of 2-6 companies on aligned fields, plus their shared and unique supply-chain counterparties. |
get_country_exposure({segment?}) | Geographic concentration: which countries host a segment's companies, ranked by count, with disclosed market-cap coverage. |
find_chokepoints({segment?, limit?}) | Rank chokepoints by downstream dependency weighted by market position. Transparent heuristic, not a proprietary risk model. |
analyze_portfolio_exposure({holdings}) | Map tickers or ids to segment/country exposure and flag suppliers that several holdings share. Not investment advice. |
| Tool | Purpose |
|---|---|
filter_companies({...}) | Structured multi-criteria screen (segment, subsegment, country, position, public, market-cap band, has_ticker) with sorting and pagination. |
list_subsegments({segment?}) | Every subsegment with its live company count and parent segment. |
get_subsegment({segment, subsegment}) | All companies in one subsegment with position and country breakdowns. |
find_similar_companies({id}) | Nearest structural neighbours by Jaccard similarity over segment tags and shared supply-chain counterparties. |
rank_by_market_cap({segment?, country?, limit?}) | Largest companies by disclosed market cap, always with its coverage ratio. |
resolve_ticker({inputs}) | Batch-resolve up to 25 tickers, names, or ids to canonical companies, with suggestions on a miss. |
| Tool | Purpose |
|---|---|
list_countries({segment?}) | Every country with company counts, segment mix, and public/private split. |
get_country_profile({country}) | One country in depth, including how many supply relationships cross its border in each direction. |
compare_countries({countries}) | 2-5 countries side by side, with uniquely-present and dominant segments. |
get_segment_leaders({segment?}) | Who occupies the monopoly and leader positions in a segment. |
get_upstream_concentration({id}) | One company's supplier mix by country and segment with an HHI index and edge-coverage context. |
| Tool | Purpose | ||
|---|---|---|---|
find_paths_between({from, to, max_depth?}) | Documented supply paths between two companies, shortest first. | ||
| `simulate_disruption({company_id? | country? | segment?})` | Blast radius if a company, country, or segment goes offline, ranking those left with no documented alternative. |
find_single_source_dependencies({segment?, country?}) | Customer/subsegment pairs served by exactly one documented supplier. | ||
rank_by_connectivity({metric?, limit?}) | Rank by documented degree. Measures documentation density, not real-world criticality. | ||
| `find_common_suppliers({ids? | segment?})` | Suppliers shared across an arbitrary set of companies, with the share of the set each serves. |
| Tool | Purpose |
|---|---|
get_deal({id}) | One M&A deal in full, with parties resolved to companies where possible. |
find_deals_by_company({id}) | Every deal a company took part in, split by role, with the match method exposed. |
get_ma_activity_summary() | Deal counts and disclosed values by year, type, and status. |
find_consolidation_hotspots() | Which segments are consolidating, with unresolvable deals counted rather than dropped. |
get_dataset_stats() | What this dataset contains, how fresh it is, and where it is thin. Call it to learn what the data cannot answer. |
Every response includes:
data — the payload.attribution — compiled-by/sources block (SEC, Wikidata, Wikipedia, GLEIF) plus a company_url back to the full sourced profile on wafergraph.com.links — { report, newsletter } pointing back to wafergraph.com and its hand-scored Vendor Exposure Review.Company records include key_products as of 2026-07-19. That field in wafergraph's own dataset was originally bulk-drafted with a known fabrication/mis-scope history and was withheld here until a verified deep-fill landed upstream; it now has (confirmed live) 564/565 companies filled, with only sk_enpulse empty (defunct, absorbed into SKC 2025-12-23). Every field shipped here — name, ticker, market_cap_usd_b, segments, one_liner, market_position, key_products, key_customers/key_suppliers graph edges, deals — is established, trust-checked data. Fields are still whitelisted (not blacklisted) in src/types.ts (toAllowedCompany), so anything added upstream later stays excluded by default until deliberately added.
Counters only, never identities. No IPs, no query contents or tool arguments, no user identifiers, no cookies, no PII. Specifically: how many times each tool was called per day, how many distinct sessions opened per day, and which client *software* connected (the clientInfo name and version your MCP client already sends in the initialize handshake, e.g. claude-code@2.1.0).
Sessions are not users — one person reconnecting counts several times. Nothing recorded here can identify who you are.
claude mcp add --transport http wafergraph https://mcp.wafergraph.com/mcp
Settings → Connectors → Add custom connector → paste:
https://mcp.wafergraph.com/mcp
{
"mcpServers": { "wafergraph": { "url": "https://mcp.wafergraph.com/mcp" } } }
Cloudflare Worker, TypeScript, built on the agents package's McpAgent (Durable-Object-backed Streamable HTTP MCP server — free on the Workers Free plan; SQLite storage backend). See CLAUDE.md for the file map and the data-source-mode decision (hybrid live-fetch + one vendored snapshot, discovered by E2E-testing the upstream endpoints rather than assumed).
npm install
npm run dev # wrangler dev, local npm run typecheck # tsc --noEmit npm run deploy # wrangler deploy
See ATTRIBUTION.md for the full source/license breakdown (SEC EDGAR public domain, Wikidata CC0, Wikipedia CC BY-SA 4.0 — attribution required, GLEIF). Short version: free to use, credit wafergraph.com, not financial advice.
This is an independent project built against wafergraph.com's public dataset; it is not an official wafergraph product.