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Wafergraph MCP

de jasonpalmer1versión 1.2.0i★ 0iSe ejecuta en la nube
Nombre en el registrocom.wafergraph/wafergraph-mcp

Instalar

Resumen

Descripción del creador (original en inglés)

Read-only MCP server for wafergraph.com's semiconductor & AI supply-chain data: 30 tools, no auth.

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en la nube
  • Transporte: Streamable HTTP
  • Categoría: Otros

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Necesitas

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Funciona en Claude para web, escritorio y móvil:

  1. Abre Settings → Connectors
  2. Presiona Add custom connector
  3. Pega la dirección de abajo y presiona Add
  4. Si te pide iniciar sesión, inicia sesión en el servicio del creador
SettingsConnectors1+ Add2https://…3Connect4
https://wafergraph-mcp.jwpalm99.workers.dev/mcp

Ejecuta esto en tu terminal

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

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

ChatGPT solo se conecta a servidores en internet:

  1. Abre ChatGPT en la web → Settings → Connectors (Apps)
  2. Presiona Create o Add (en algunos planes primero hay que activar Developer mode en Advanced)
  3. Pega la dirección de abajo, ponle un nombre y guarda
  4. Si te pide iniciar sesión, inicia sesión en el servicio del creador
SettingsConnectors1+ Create2https://…3Connect4
https://wafergraph-mcp.jwpalm99.workers.dev/mcp

Los nombres de los menús pueden variar un poco según el plan y con el tiempo.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué apps pueden usarlo

Según cómo se conecta este servidor y la documentación de cada app, comprobado el 10 nov 2026.

Se conectan por internet en

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

Todas las apps, con ventajas y desventajas →

Qué puede hacer

Nombres y descripciones de las herramientas tal como los informó el servidor el 10 nov 2026. Los escribió el creador, no nosotros; los mostramos como texto sin formato.

  • 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

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 11 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con el dominio wafergraph.com (el registro comprueba quién es dueño del dominio)

  • ✓ Superada

    Sigue en mantenimiento

    Último cambio de código: hace 2 meses

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • ✓ Superada

    El endpoint responde

    Respondió en 637 ms (HTTP 200)

  • – No aplica

    Inicio de sesión con OAuth

    No hace falta iniciar sesión

  • ✓ Superada

    Sin instrucciones ocultas en las descripciones de herramientas

    Leímos 30 descripciones de herramientas y no encontramos instrucciones ocultas para la IA

Comparado con otros en Otrosi

  • Más estrellas que el 0% de los otros 19101 servidores de esta categoría
  • Publicado en el registro más recientemente que el 17% de los otros 19101 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 19101 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Wafergraph MCP?

Superó 4 de 4 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez hace 2 meses, y la última versión (1.2.0) llegó al registro hace 3 meses.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.

¿Qué puedo usar en su lugar?

En la misma categoría: World Monitor, Claude Flow, Tldraw

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

World Monitor

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

de koala73Muy usado★ 90,4 milActualizado hace 6 días

Se ejecuta en la nube✓ worldmonitor.app

Claude Flow

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

de ruvnetMuy usado↓ 13,5 mil/sem★ 81,4 milActualizado hace 14 meses

Se ejecuta en tu computadora

Tldraw

Draw and visually collaborate with your agents on tldraw's canvas.

de tldrawMuy usado★ 51,4 milActualizado hace 8 meses

Se ejecuta en la nube

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

wafergraph-mcp

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

Tools

ToolPurpose
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.
Screening & discovery
ToolPurpose
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.
Geography & structure
ToolPurpose
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.
Graph analysis
ToolPurpose
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.
Deals & dataset
ToolPurpose
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.
Field discipline

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.

What this server records

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.

Install

Claude Code
claude mcp add --transport http wafergraph https://mcp.wafergraph.com/mcp
claude.ai (custom connector)

Settings → Connectors → Add custom connector → paste:

https://mcp.wafergraph.com/mcp
Generic MCP client (Streamable HTTP)
{

"mcpServers": { "wafergraph": { "url": "https://mcp.wafergraph.com/mcp" } } }

Architecture

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).

Development

npm install

npm run dev # wrangler dev, local npm run typecheck # tsc --noEmit npm run deploy # wrangler deploy

Attribution & licensing

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.