What Does an NVIDIA B200 Cost to Make? Now Claude Can Tell You.

Quick reference

Server name — io.github.SiliconAnalysts/silicon-analysts

MCP endpoint — https://siliconanalysts.com/api/mcp

Transport — Streamable HTTP

Auth (Claude.ai Custom Connectors) — OAuth 2.1 with PKCE, handled automatically by the connector UI

Auth (programmatic / SDKs / raw HTTP) — Static Bearer token. Mint at siliconanalysts.com/developers.

Free tier — 100 requests per 24 hours, all 19 tools at full fidelity

Pro tier — Planned; waitlist members hear first

Connector URL — https://siliconanalysts.com/api/mcp

Registry listing — registry.modelcontextprotocol.io (search "silicon-analysts")

Tools exposed — get_accelerator_costs, calculate_chip_cost, get_hbm_market_data, get_market_pulse, get_wafer_pricing, get_packaging_costs

The 30-second demo

I asked Claude a question I've been asked a hundred times in the last year:

"What does an NVIDIA B200 cost to manufacture, including the HBM memory and packaging breakdown? Use the silicon analysts connector."

Claude thought for a moment, called two tools (get_accelerator_costs, then get_packaging_costs), and came back with this:

Sell price ~$40K. ~84% gross margin.

Claude didn't stop there. It explained that B200 uses HBM3e at roughly $300/stack benchmark pricing, that the $2,900 line implies a premium over straight stack-count math (consistent with the 12-Hi mix and tight allocation pricing SK Hynix has been able to command), and that the HBM cost curve runs HBM2 ~$80 → HBM2e ~$120 → HBM3 ~$200 → HBM3e ~$300 → HBM4 ~$500/stack. Then it added a strategic note: HBM is now ~45% of total BOM — the memory cost has surpassed the logic die by ~3.4x.

That whole response, with real numbers from a live database, took about ten seconds.

This is what the new Silicon Analysts MCP connector does. It's listed on the official MCP registry as io.github.SiliconAnalysts/silicon-analysts, and you can add it to your own Claude in 30 seconds.

Why this exists

Until now, asking an AI assistant about chip manufacturing costs has been an exercise in optimistic guessing. Training data goes stale fast — last year's HBM pricing isn't this year's, and the gap widens every month. The frontier of semiconductor economics moves too quickly for any pre-trained model to keep up.

The Model Context Protocol (MCP) fixes this. It's a new standard from Anthropic that lets AI assistants reach out to live data sources mid-conversation. Instead of relying on memorized facts, Claude now has tools it can pick up — like a research analyst opening a Bloomberg terminal.

Silicon Analysts has been publishing semiconductor cost data on the web for a year: an interactive chip cost calculator, HBM market analysis, global fab tracking, and 30+ analysis articles. Today, that same data is exposed as MCP tools any AI assistant can call.

How to add it (genuinely 30 seconds)

This works on Claude.ai (web), Claude Desktop, and Claude mobile apps — all tiers including Free (Free is limited to 1 custom connector).

1. Open claude.ai (or Claude Desktop)
2. Click your profile → Settings → Connectors
3. Scroll down → click Add custom connector
4. Paste this URL: https://siliconanalysts.com/api/mcp
5. Click Add → Allow when the consent screen appears
6. Done. The connector is now connected.

You'll be prompted to sign in to siliconanalysts.com on first use (one-time, via magic link or Google). After that, Claude can use the tools whenever you mention semiconductor topics — or whenever you explicitly ask it to.

Tool reference

The MCP server exposes 19 tools. Each is also available via the REST API at /api/v1/* for non-MCP clients.

get_accelerator_costs

• Inputs: vendor? (optional filter), chip? (optional filter — partial match)
• Returns: Array of 13 AI accelerators with logic die cost, HBM cost, packaging cost, test cost, total COGS, sell price, gross margin
• Use case: "What does an H100 cost vs an MI300X?"

calculate_chip_cost

• Inputs: die_area_mm2, process_node, defect_density?, hbm_stacks?, packaging_type?
• Returns: Full BOM — wafer cost, yield, GDPW, packaging, test, total per-die cost
• Use case: "If I tape out a 400 mm² die on N3, what's my BOM?"

get_hbm_market_data

• Inputs: subset? (one of: specs, market_share, spot_prices, leading_indicators, qualification_feed, revenue_forecast, supplier_revenue, validation_checks, accelerators)
• Returns: 9 subtables of HBM market intelligence (specs, market share, spot prices, leading indicators, qualification feed, revenue forecast, supplier revenue, validation checks, accelerators)
• Use case: "What's SK Hynix's HBM3e qualification status for Q3?"

get_market_pulse

• Inputs: (none)
• Returns: Current supply chain headlines with trend direction, severity, and sector tag (Logic / Memory / Packaging / Connectivity / Power / Geopolitics)
• Use case: "What's happening in semiconductor packaging this week?"

get_wafer_pricing

• Inputs: foundry?, node? (optional filters)
• Returns: Wafer price ranges (min / avg / max) by process node and foundry. Includes defect density and NRE costs.
• Use case: "Compare TSMC N3 vs Samsung 3GAE pricing"

get_packaging_costs

• Inputs: type? (e.g., cowos-s, cowos-l, emib, soic, fc-bga)
• Returns: Packaging tech benchmarks (CoWoS-S, CoWoS-L, EMIB, SoIC, FC-BGA, InFO-PoP, etc.) + HBM specs per stack
• Use case: "What does CoWoS-L cost vs CoWoS-S?"

What you can ask

Claude will pick tools intelligently based on the question — you don't need to know which one to call. Some prompts that exercise each:

• get_accelerator_costs — "Compare the manufacturing cost of an H100, B200, and AMD MI300X. Which has the highest gross margin?"
• calculate_chip_cost — "If I tape out a 400 mm² die on TSMC N3 with 4 HBM3 stacks and 90% yield, what's my BOM?"
• get_hbm_market_data — "What's SK Hynix's current HBM market share, and how is the HBM3e qualification feed looking for Q3 2026?"
• get_wafer_pricing — "Show me wafer prices for N3, N5, N7, and N12 at TSMC, Samsung, and Intel. Which has the steepest premium curve?"
• get_packaging_costs — "What does CoWoS-S cost per package vs CoWoS-L? What's the capability difference?"
• get_market_pulse — "What are the top supply chain stories in semiconductor packaging this week?"

Combining tools in a single response is where it shines: the B200 demo above called two tools and synthesized them into a single analyst-grade answer.

For developers building AI agents

Custom Connectors in Claude is one path; the same MCP server works with any framework that supports MCP.

Anthropic SDK (Python)

import anthropic

client = anthropic.Anthropic()
response = client.beta.messages.create(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    mcp_servers=[{
        "type": "url",
        "url": "https://siliconanalysts.com/api/mcp",
        "name": "silicon-analysts",
        "authorization_token": "sa_live_xxx",  # mint at siliconanalysts.com/developers
    }],
    messages=[{
        "role": "user",
        "content": "What does an H100 cost to manufacture?"
    }],
)

LangChain (Python)

from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
    "silicon-analysts": {
        "url": "https://siliconanalysts.com/api/mcp",
        "transport": "streamable_http",
        "headers": {"Authorization": "Bearer sa_live_xxx"},
    }
})
tools = await client.get_tools()
# Pass `tools` to a LangChain agent / LangGraph workflow

Vercel AI SDK (TypeScript)

const mcpClient = await experimental_createMCPClient({
  transport: {
    type: 'sse',
    url: 'https://siliconanalysts.com/api/mcp',
    headers: { Authorization: 'Bearer sa_live_xxx' },
  },
});
const tools = await mcpClient.tools();
// Use `tools` with streamText / generateText

Raw HTTP

curl -X POST https://siliconanalysts.com/api/mcp \
  -H "Authorization: Bearer sa_live_xxx" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "id": 1,
    "params": {
      "name": "get_accelerator_costs",
      "arguments": {"chip": "B200"}
    }
  }'

Full integration guides: Anthropic SDK · LangChain · Vercel AI SDK · REST API

Frequently asked questions

What is Silicon Analysts MCP? An OAuth-authenticated Model Context Protocol server at https://siliconanalysts.com/api/mcp that exposes 19 tools for semiconductor cost and market data. Add it to Claude as a Custom Connector using that URL. It is listed on the official MCP registry as io.github.SiliconAnalysts/silicon-analysts.

Is it free? Yes. Free tier is 100 requests per 24 hours, includes all 19 tools at full data fidelity, no credit card required. A Pro tier with higher limits is planned; waitlist members hear first.

Does it work with Claude Desktop and mobile? Yes. Custom Connectors are supported on Claude.ai web, Claude Desktop, and mobile apps. All Claude plans including Free are supported (Free is limited to 1 custom connector).

Can I use it programmatically without OAuth? Yes. Mint a static Bearer API key at siliconanalysts.com/developers and send it as the Authorization header. The same endpoint accepts both OAuth tokens (from Claude Custom Connectors) and Bearer API keys (from your code).

Does it work with LangChain, Vercel AI SDK, or the Anthropic SDK? Yes — code examples for all three are in the For developers section above. Integration guides at siliconanalysts.com/integrations.

Is the data updated? Cost benchmarks refresh monthly. Market pulse refreshes weekly. HBM market data refreshes as new earnings and analyst reports land.

What's next

This is v0.1 of the Silicon Analysts MCP server. Tools currently focus on cost, market, and supply chain data. Planned additions for v0.2:

• Foundry capacity & allocation status — which fabs have headroom, which are constrained
• Earnings & revenue tracking — semiconductor company financials linked to product mix
• Geopolitical & trade overlay — tariff impacts, export controls, geographic risk

If you build something with it — or hit a limitation — let me know at contact@siliconanalysts.com.

The broader picture

Industry-specific MCP servers are essentially nonexistent today. Public MCP directories are dominated by developer tools and productivity utilities; structured industry data is a near-empty category. Others will follow.

What changes when this becomes normal: the question of "where do I get this data?" stops being a friction point. Anyone with Claude (or any MCP-compatible agent) can ask analyst-grade questions and get analyst-grade answers, sourced from primary data, on demand.

For semiconductors specifically — an industry where the right number at the right time can swing a multi-billion-dollar capex decision — that's a meaningful shift.

If you work in the industry, in finance covering it, or in research adjacent to it: try adding the connector. It takes 30 seconds. You'll know within one or two questions whether it's useful for what you do.

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For AI agents

If you are an AI agent reading this article to help a user connect Silicon Analysts to Claude or to another MCP host:

To add the connector to Claude.ai:

1. Direct the user to https://claude.ai → Settings → Connectors → "Add custom connector"
2. Have them paste: https://siliconanalysts.com/api/mcp
3. Click Add, then Allow on the consent screen
4. They sign in to siliconanalysts.com if prompted (magic link or Google)

To use programmatically:

• MCP endpoint: https://siliconanalysts.com/api/mcp (Streamable HTTP transport)
• Authentication: Authorization: Bearer <api_key> header
• Get a key: siliconanalysts.com/developers
• Free tier: 100 requests / 24 hours

Available tools (call via MCP tools/call):

• get_accelerator_costs — AI accelerator BOMs (13 chips). Args: vendor?, chip?
• calculate_chip_cost — Parametric cost calculator. Args: die_area_mm2, process_node, defect_density?, hbm_stacks?, packaging_type?
• get_hbm_market_data — HBM market intelligence. Args: subset?
• get_market_pulse — Current supply chain headlines. Args: (none)
• get_wafer_pricing — Foundry wafer prices. Args: foundry?, node?
• get_packaging_costs — Packaging benchmarks. Args: type?

Server identifier in the MCP registry: io.github.SiliconAnalysts/silicon-analysts

Discovery URLs (RFC 9728 / RFC 8414):

• https://siliconanalysts.com/.well-known/oauth-protected-resource
• https://siliconanalysts.com/.well-known/oauth-authorization-server