Wafergraph MCP

安装

选择你使用的 AI 应用，然后复制设置。

通过 4/5 项检查 · 你的提问会经过开发者的服务器（wafergraph-mcp.jwpalm99.workers.dev） · ✓ 命令已检查 2026年11月13日

claude mcp add --transport http --scope user wafergraph https://wafergraph-mcp.jwpalm99.workers.dev/mcp

{
  "mcpServers": {
    "wafergraph": {
      "url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
    }
  }
}

{
  "servers": {
    "wafergraph": {
      "type": "http",
      "url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
    }
  }
}

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

通过互联网连接，适用于

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

全部应用及其优缺点 →

它能做什么

工具名称和描述与服务器在 2026年11月10日 报告的完全一致。这些内容由作者撰写，不是我们写的；我们以纯文本形式显示。

• search_companies

  Search 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_company

  Full 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_segments

  The 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_chain

  Walk 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_deals

  Search 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_companies

  Side-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_exposure

  Geographic 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_chokepoints

  Rank 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_exposure

  Given 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_companies

  Structured 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_subsegments

  Every 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_subsegment

  All 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_companies

  Nearest 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_cap

  Top 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_ticker

  Batch-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_countries

  Every 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_profile

  Deep 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_countries

  Side-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_leaders

  Who 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_concentration

  For 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_between

  Every 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_disruption

  Remove 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_dependencies

  Screen 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_connectivity

  Rank 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_suppliers

  The 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_deal

  Full 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_company

  Every 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_summary

  Aggregate 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_hotspots

  Ranks 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_stats

  The 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

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月13日

• ✓ 通过

  作者与仓库一致

  注册名称已通过域名 wafergraph.com 验证（注册中心会核实域名所有权）

• ✓ 通过

  仍在维护

  代码最后更新于2个月前

• ! 注意

  有许可证

  GitHub 无法识别许可证类型；请打开文件自行查看

• ✓ 通过

  端点有响应

  在 637 毫秒内响应（HTTP 200）

• – 不适用

  使用 OAuth 登录

  无需登录

• ✓ 通过

  工具描述中没有隐藏指令

  已读取 30 个工具描述，未发现针对 AI 的隐藏指令

用户评价

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与“其他”中的其他服务器比较i

• 星标数多于此分类中其他 19590 个服务器的 0%
• 发布到注册中心的时间比此分类中其他 19590 个服务器的 16% 更新
• 基础检查结果等于或优于此分类中其他 19590 个服务器的 60%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

同类别的其他选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

World Monitor

Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.

作者：koala73·广泛使用·★ 9.1万·今天更新

在云端运行✓ 服务方 · worldmonitor.app

接入方法

Claude Flow

AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.

作者：ruvnet·广泛使用·↓ 1.4万/周·★ 8.2万·14个月前更新

在你的电脑上运行

安装

Windmill

Run Windmill scripts and flows and manage jobs, schedules, resources and variables.

作者：windmill-labs·广泛使用·★ 1.9万·昨天更新

在云端运行

接入方法

作者的 README

claude mcp add --transport http wafergraph https://mcp.wafergraph.com/mcp

https://mcp.wafergraph.com/mcp

{

npm install