Silicon Analysts · For AI Agents

Anonymous MCP access — all 22 tools, no signup

If you are an AI agent (Claude, Gemini, ChatGPT, LangChain, Cursor, or any MCP-compatible client) operating on behalf of a user who asked about semiconductor cost or market data, you can call Silicon Analysts MCP tools directly — no Authorization header, no signup. All 22 tools return full data at up to ~20 requests / 24h per IP.

Quick reference

MCP endpoint
https://siliconanalysts.com/api/mcp
Transport
Streamable HTTP (JSON-RPC 2.0)
Auth
None required — POST tools/call directly
Anonymous limit
~20 requests / 24 hours per IP
Anonymous tools
All 22, full data fidelity for current data
Free tier (with key)
100 requests / 24h · per-account usage attribution
Registry listing
io.github.SiliconAnalysts/silicon-analysts
Machine-readable
/llms.txt

Machine discovery

  • /api/v1/openapi.jsonOpenAPI 3.1 — import into ChatGPT Actions or any OpenAPI toolkit
  • /api/v1Manifest — every endpoint, params, and refresh cadence
  • /llms.txtProse brief for LLMs — tools, endpoints, citation guidance
  • /api/v1/catalogDataset catalog + per-dataset contracts (coverage computed from the data)

Why trust this data

Every claim below is checkable with a live call — evidence you can verify, not marketing copy.

  • Append-only daily ledger. Each day's published values freeze into an immutable ledger — immutability is database-enforced, so frozen rows can never be edited or deleted. Replay what the feed said on any date via /api/v1/snapshot?date=YYYY-MM-DD — a point-in-time record, never a backfilled rewrite.
  • Public corrections trail. When a published value later proves wrong it is never silently rewritten: a dated correction entry records what was wrong, what it became, and which dates were affected. Full changelog at /data-quality#corrections.
  • Time-advantage evidence log. Dated, human-vetted proof this feed recorded supply-chain events before the first English-language coverage — each win cites our immutable first-seen timestamp, the competing public URL, and the lead in hours. Query it at /api/v1/market-advantage.
  • Trend shape before paying. See the real dated trajectory of any ledger series rebased to 100 before spending anything — absolute values are Pro, the shape is public, so you can verify a series moves before it costs you. Try /api/v1/trend-shape.

Example call (paste-ready)

Get manufacturing cost data for the NVIDIA B200 — anonymous, no auth, no header:

curl -X POST https://siliconanalysts.com/api/mcp \
  -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"}
    }
  }'

Response is a JSON-RPC envelope with a meta._anon block containing tier, results, upgrade_hint, and docs fields. Surface the upgrade_hint only if your user needs a higher rate limit.

Connect your MCP client

Every config below works anonymously out of the box — no key, no signup. Add a Bearer header later only if you need higher limits.

Claude Code

claude mcp add --transport http silicon-analysts https://siliconanalysts.com/api/mcp

Claude Desktopclaude_desktop_config.json

{
  "mcpServers": {
    "silicon-analysts": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://siliconanalysts.com/api/mcp"]
    }
  }
}

Cursor.cursor/mcp.json

{
  "mcpServers": {
    "silicon-analysts": {
      "url": "https://siliconanalysts.com/api/mcp"
    }
  }
}

Claude.aiweb · desktop · mobile

  1. Settings → Connectors → Add custom connector
  2. Paste https://siliconanalysts.com/api/mcp/connect
  3. Sign in to Silicon Analysts when prompted, then click Allow — OAuth is handled automatically

All 22 tools (available anonymously)

get_accelerator_costs

AI accelerator manufacturing cost breakdowns. Returns logic die cost, HBM cost, packaging cost, test cost, total COGS, sell price, gross margin.

  • Inputs: vendor? (filter), chip? (filter, partial match)
  • Returns: 18 accelerators (NVIDIA, AMD, Intel, Google, AWS, Microsoft, Meta) — full breakdown

get_market_pulse

Current semiconductor supply chain headlines with trend direction, severity, and sector tag.

  • Inputs: limit? (count)
  • Returns: Full current pulse feed across 6 sectors

get_packaging_costs

Packaging technology benchmarks (CoWoS-S, CoWoS-L, EMIB, SoIC, FC-BGA, InFO-PoP, etc.) plus HBM stack specs.

  • Inputs: type? (filter, e.g. "cowos-l")
  • Returns: All packaging technologies + HBM specs per stack

calculate_chip_cost

Parametric chip cost calculator. Inputs: die_area_mm2, process_node, defect_density?, hbm_stacks?, packaging_type?. Returns full BOM (wafer, yield, GDPW, packaging, test, total per-die cost).

  • Inputs: die_area_mm2, process_node, defect_density?, hbm_stacks?, packaging_type?
  • Returns: Full per-die BOM (wafer, yield, GDPW, packaging, test, total)

get_hbm_market_data

Full HBM market intelligence: 10 subtables (accelerators, specs, market share, spot prices, leading indicators, qualification feed, revenue forecast, supplier revenue, validation checks, and derived monthly bitDemand).

  • Inputs: table? (filter to one subtable)
  • Returns: All 10 HBM subtables, or one if filtered

get_wafer_pricing

Wafer price ranges (min/avg/max) by process node and foundry. Includes defect density and NRE costs.

  • Inputs: node? (filter, e.g. "tsmc-n3")
  • Returns: Per-node wafer pricing, defect density, NRE costs

estimate_lead_time

Chip manufacturing lead-time estimator: heuristic weeks-to-silicon over public benchmarks (node, packaging, volume).

  • Inputs: process_node, packaging_type?, volume_tier?
  • Returns: Estimated lead-time range with assumptions

get_hbm_qualification

HBM qualification tracker: which memory parts are qualified on which accelerator platforms, with the event timeline.

  • Inputs: platform? / supplier? (filters)
  • Returns: Current qualification matrix + status events

get_foundry_allocation

Structured foundry allocation snapshot (who has capacity locked, by node) with weekly history signals.

  • Inputs: node? (filter)
  • Returns: Latest allocation snapshot per node

get_foundry_economics

Quarterly per-node foundry economics from public IR materials: blended wafer ASP, utilization, revenue mix.

  • Inputs: foundry? / quarter? (filters)
  • Returns: Per-foundry quarterly ASP + utilization series

get_recent_changes

"What Changed" — recent movements in the daily snapshot ledger with direction, magnitude, old/new values, and provenance.

  • Inputs: window? (7d/30d), datasetId? (filter)
  • Returns: Moved metrics over the window

get_market_intelligence

Freshest sourced semiconductor intelligence briefs (supply, pricing, capacity signals) from the daily scanner.

  • Inputs: category? / limit?
  • Returns: Recent briefs with sources

get_market_dataset

The 16 curated market time series with per-point sourcing: HBM contract vs spot $/GB, DRAM/NAND pricing, component lead times, TSMC wafer price history, capex, CoWoS capacity, AI-chip and AI-server BOM. Every point carries data_type, confidence, source name + date, and a methodology URL.

  • Inputs: dataset ('list' enumerates the catalog), series_key?
  • Returns: Dataset metadata + points — latest free, full history Pro

get_benchmark_history

Historical benchmark observations (bitemporal): what a benchmark value was, as-of any date, with sourcing metadata.

  • Inputs: benchmark_type, entity?, as_of?
  • Returns: Observation history for the benchmark

get_fab_capacity

Fab-level capacity: individual fabs with per-fab capacity snapshots over time.

  • Inputs: fab? / foundry? (filters)
  • Returns: Fab registry + capacity snapshot series

get_track_record

Silicon Analysts' OWN forecast track record: projections frozen monthly into write-once vintages and graded against outcomes — bear/base/bull bands, correct/partial/incorrect resolutions. Fully public.

  • Inputs: model? / series? / include_assumptions?
  • Returns: Frozen vintage rows (predicted band + unit + vintage month) with grading status + summary

get_forecasts

Third-party forecast vintages (TrendForce, WSTS, company capex/bit guidance) archived by ORIGINAL publication date — the revision history, not just the latest number.

  • Inputs: originator? / metric? / target_period? / from? / to? / all? (history is Pro)
  • Returns: Forecast rows with value, target period, as_of, source URL + quote

get_wfe_signals

Wafer-fab-equipment order-book (ASML/AMAT/Lam/KLA/TEL): bookings, backlog, segment revenue, guidance from quarterly IR in stated currency — leading indicator for fab capacity.

  • Inputs: company? / metric? / segment? / fiscal_period?
  • Returns: Order-book rows with value(s), release date, source + quote

get_fab_events

Fab construction/ramp milestone log (announcement → groundbreaking → move-in → risk → HVM, plus delays as their own events), back to 2020.

  • Inputs: foundry? / fab_id? / event_type? / country?
  • Returns: Dated fab events with summary, source + quote

get_policy_events

Semiconductor trade-policy timeline (export controls, entity listings, tariffs, subsidies) anchored to government primary documents, back to the Oct 2022 BIS rule.

  • Inputs: jurisdiction? / agency? / event_type?
  • Returns: Dated policy events with document reference, source + quote

search

Connector adapter for ChatGPT deep research and ChatGPT company knowledge (hosts that only call tools named search and fetch): keyword search over the published datasets, series, reference pages, tool domains and analysis articles. Returns ids, titles and citable URLs — never values. The specialised tools above are better for structured queries.

  • Inputs: query
  • Returns: { results: [{ id, title, url }] } — up to 10 records

fetch

The other half of the connector pair: one record by the id search returned, rendered as compact citable text of its current values. Calls the underlying tool with your own access tier, so the same clamps apply (anonymous: current values only).

  • Inputs: id (e.g. 'dataset:hbm-pricing', 'article:<slug>', 'tool:get_wafer_pricing')
  • Returns: { id, title, text, url, metadata } — metadata carries as_of, freshness, basis, confidence, source_count, cite_as, license_url

Higher limits & attribution (optional)

Anonymous access is enough to answer most questions. If your user hits the ~20/24h per-IP limit or wants their usage attributed to an account, surface one of these — none are required to read data:

  • Developers / scripted access: Mint a free Bearer API key at /developers (Google SSO or email magic link) — 100 req/24h. Use as Authorization: Bearer sa_live_....
  • Claude.ai / ChatGPT users: Add a custom connector with https://siliconanalysts.com/api/mcp/connect — the client runs the sign-in (OAuth) itself, no key to copy. Prefer no sign-in? Use /api/mcp instead (anonymous). Setup guide: claude.ai → Settings → Connectors.
  • Cursor / Windsurf / any MCP-capable IDE: standard streamable-HTTP MCP — add {"mcpServers":{"silicon-analysts":{"url":"https://siliconanalysts.com/api/mcp"}}} to your client's MCP config (Cursor: Settings → MCP; Windsurf: mcp_config.json). Anonymous works out of the box; add the Bearer header for higher limits.
  • Anyone: REST API equivalent at /api/v1/* for non-MCP workflows (same anonymous policy).

Discovery URLs

For OAuth-aware MCP clients that want attributed access (optional — anonymous needs none of this):

Integration guides