Use Silicon Analysts with the Anthropic SDK
Give Claude live access to AI accelerator costs, wafer pricing, packaging benchmarks, and HBM market data — all through Anthropic’s MCP connector. Works in Python and TypeScript, server or serverless.
Prerequisites
- An Anthropic API key from console.anthropic.com. Set it as
ANTHROPIC_API_KEY. - A Silicon Analysts API key from /developers. Set it as
SA_API_KEY. Free tier: 100 requests per 24h. - Python 3.10+ or Node.js 18+, plus the official Anthropic SDK (
anthropic).
Quickstart — Python
Install the SDK, then call the Messages API with an mcp_servers block. Claude discovers Silicon Analysts’ six tools automatically and calls them as needed.
pip install anthropic
# claude_with_silicon_analysts.py
import os
from anthropic import Anthropic
client = Anthropic() # reads ANTHROPIC_API_KEY from env
response = client.beta.messages.create(
model="claude-sonnet-4-5",
max_tokens=1024,
messages=[{
"role": "user",
"content": "What's the manufacturing cost breakdown for an NVIDIA H100? "
"Compare it to the B200."
}],
mcp_servers=[{
"type": "url",
"url": "https://siliconanalysts.com/api/mcp",
"name": "silicon-analysts",
"authorization_token": os.environ["SA_API_KEY"],
}],
betas=["mcp-client-2025-04-04"],
)
for block in response.content:
if block.type == "text":
print(block.text)Run it: python claude_with_silicon_analysts.py. Claude will call get_accelerator_costs under the hood and synthesize the comparison.
Quickstart — TypeScript
Same pattern in TypeScript. Drop this into a Next.js route handler, a Vercel function, or a standalone script.
npm install @anthropic-ai/sdk
// claude-with-silicon-analysts.ts
import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic(); // reads ANTHROPIC_API_KEY from env
const response = await client.beta.messages.create({
model: 'claude-sonnet-4-5',
max_tokens: 1024,
messages: [{
role: 'user',
content:
"What's the current wafer price range for TSMC N3, and how has " +
"HBM3e pricing trended?",
}],
mcp_servers: [{
type: 'url',
url: 'https://siliconanalysts.com/api/mcp',
name: 'silicon-analysts',
authorization_token: process.env.SA_API_KEY!,
}],
betas: ['mcp-client-2025-04-04'],
});
for (const block of response.content) {
if (block.type === 'text') console.log(block.text);
}Realistic Use Case: Tapeout Cost Estimator Agent
A more useful example: an agent that helps a fabless startup estimate tapeout cost. It uses three tools in sequence — get_wafer_pricing, calculate_chip_cost, and get_packaging_costs. You write the natural-language question; Claude orchestrates the tool calls.
response = client.beta.messages.create(
model="claude-sonnet-4-5",
max_tokens=2048,
system=(
"You are a semiconductor cost analyst. When the user asks about chip "
"economics, use the silicon-analysts MCP tools to ground your answer "
"in current data. Cite the provenance.last_updated field."
),
messages=[{
"role": "user",
"content": (
"I'm taping out a 200mm² SoC on TSMC N4 with one HBM3e stack and "
"CoWoS-S packaging. Estimate the per-die cost and the BOM. "
"What's the typical mask-set NRE at this node?"
)
}],
mcp_servers=[{
"type": "url",
"url": "https://siliconanalysts.com/api/mcp",
"name": "silicon-analysts",
"authorization_token": os.environ["SA_API_KEY"],
}],
betas=["mcp-client-2025-04-04"],
)get_wafer_pricing for N4, then calculate_chip_cost with the 200mm² die area and the wafer price it just retrieved, then get_packaging_costs for CoWoS-S and HBM3e. Each tool returns a provenance block so the model can hedge appropriately.Production Tips
1. Cache responses where the data is stable
Wafer pricing, packaging costs, and accelerator BOMs refresh on a monthly-to-quarterly cadence. Cache the MCP responses (or the Claude responses) for at least 1 hour to stay well under your rate-limit budget. The provenance.last_updated timestamp tells you when to invalidate.
2. Handle rate limits gracefully
When the Silicon Analysts server returns JSON-RPC error code -32004 (rate-limit exceeded), Claude will surface the error to the user. Catch it and either back off or upgrade to the Pro tier (10,000 req/hr). The free tier’s 100 req/24h is calibrated for development and agent usage; production traffic should run on Pro.
3. Use a dedicated key per environment
Generate separate API keys for development, staging, and production on /developers. You’ll get clean per-environment usage analytics and can rotate one without breaking the others.
4. Tell Claude about provenance in the system prompt
Models tend to drop confidence and freshness signals in their final output unless prompted. Add a sentence like “Always cite the provenance.last_updated field when reporting numbers” and the model will surface freshness — useful for procurement and finance audiences.
5. Stream long responses
For multi-tool workflows the response can take 5-15 seconds. Use the SDK’s streaming API (client.beta.messages.stream(...)) to ship tokens to the user as they arrive.
Frequently Asked Questions
How do I use Silicon Analysts with the Anthropic SDK?
Pass an mcp_servers configuration block to the Anthropic Messages API pointing at https://siliconanalysts.com/api/mcp with your Silicon Analysts API key as the authorization_token. Claude will discover and call the available tools automatically.
Do I need an Anthropic API key and a Silicon Analysts API key?
Yes — both. The Anthropic key authenticates your Claude calls. The Silicon Analysts key authenticates Claude when it reaches out to the Silicon Analysts MCP server on your behalf. The free Silicon Analysts tier allows 100 requests per 24 hours.
What MCP tools are available?
Six tools: get_accelerator_costs (13 AI chips), calculate_chip_cost (cost from die dimensions), get_hbm_market_data (HBM market intelligence), get_market_pulse (supply-chain headlines), get_wafer_pricing (wafer prices by node), and get_packaging_costs (packaging benchmarks).
What is the rate limit?
Free tier: 100 requests per 24 hours per API key. Pro tier: 10,000 requests per hour. Anonymous (no key): 10 requests per 24 hours by IP. The MCP server returns a JSON-RPC -32004 error when limits are exceeded.
Does each tool response include data freshness and provenance?
Yes. Every record returned by every tool carries a provenance block with last_updated (ISO 8601), source_type (research, derived, computed, estimated), confidence_tier (high, medium, low), and dataset_version. See /data-quality for the canonical schema.
Can I use the Anthropic SDK with MCP from a serverless function?
Yes. The Silicon Analysts MCP server uses streamable HTTP transport (stateless), so each Anthropic Messages call is fully self-contained. Works from Vercel, Cloudflare Workers, AWS Lambda, and any other serverless platform.