Wafergraph is an MCP server with 30 tools an agent can call, among them analyze_portfolio_exposure, compare_companies, compare_countries. It answers at https://wafergraph-mcp.jwpalm99.workers.dev/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 6 of 6 times since 10 September 2026; the last check, on 19 October 2026, succeeded.
Read-only MCP server for wafergraph.com's semiconductor & AI supply-chain data: 30 tools, no auth.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
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 suppl Inputs: holdings |
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. Inputs: ids |
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. co Inputs: countries |
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 fi Inputs: segment, subsegment, country, market_position, public, min_market_cap_usd_b |
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 tran Inputs: segment, limit |
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'), w Inputs: company_ids, segment, limit |
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 par Inputs: limit, sort_by |
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 i Inputs: company |
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 o Inputs: from, to, max_depth, direction, limit |
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 Inputs: id, limit |
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 coun Inputs: segment, country, limit |
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 REA Inputs: id |
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 Inputs: segment |
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/outboun Inputs: country |
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 |
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 Inputs: id |
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. Inputs: query, segment |
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 wit Inputs: top_n |
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 p Inputs: segment |
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_compa |
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 f Inputs: segment, subsegment, limit, offset |
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. Inputs: id, direction, depth |
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 on Inputs: id |
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 comp Inputs: segment |
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_s Inputs: segment |
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 t Inputs: metric, segment, country, limit |
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 Inputs: limit, segment, country, market_position |
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; unresolve Inputs: queries |
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 Inputs: query, segment, country |
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 sa Inputs: company_id, country, segment, limit |
Every block below points at https://wafergraph-mcp.jwpalm99.workers.dev/mcp. Pick your client and copy.
claude mcp add --transport http wafergraph https://wafergraph-mcp.jwpalm99.workers.dev/mcp
{
"mcpServers": {
"wafergraph": {
"command": "npx",
"args": ["-y", "mcp-remote", "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"
}
}
}{
"context_servers": {
"wafergraph": {
"url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}{
"mcpServers": {
"wafergraph": {
"serverUrl": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}{
"mcpServers": {
"wafergraph": {
"url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}name: Wafergraph
version: 0.0.1
schema: v1
mcpServers:
- name: Wafergraph
type: streamable-http
url: https://wafergraph-mcp.jwpalm99.workers.dev/mcp{
"mcpServers": {
"wafergraph": {
"httpUrl": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}{
"mcpServers": {
"wafergraph": {
"type": "http",
"url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}{
"mcpServers": {
"wafergraph": {
"url": "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fwafergraph-mcp.jwpalm99.workers.dev%2Fmcp&type=streamable_http&id=wafergraph&name=Wafergraph
It answered our last check on 19 October 2026 in 300 ms. Over 6 checks since 10 September 2026 it answered 6. Status here comes from Neuronto's own probes, not from the publisher.
30, as returned by the server's own tools/list on 11 September 2026: analyze_portfolio_exposure, compare_companies, compare_countries, filter_companies, find_chokepoints, find_common_suppliers, find_consolidation_hotspots, find_deals_by_company, and 22 more.
It answered our last check on 19 October 2026 in 300 ms. Over 6 checks since 10 September 2026 it answered 6.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://wafergraph-mcp.jwpalm99.workers.dev/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: com.wafergraph. Endpoint host: wafergraph-mcp.jwpalm99.workers.dev. ARD identifier: urn:air:com.wafergraph:mcp:wafergraph-mcp.
First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.