mineral-intel-benchmark

Mineral intelligence API: 8 critical minerals (USGS benchmarks) with mineral processing and ultrasound run-log data.

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What it can do

  • Sales.Ask: Ask anything about this API: what commodities are covered, how on-chain provenance works, pricing tiers, x402 payment flow, MCP integration, or the Extract API. Free to call. Returns a natu
  • Benchmark.Commodity: Returns USGS Mineral Commodity Summaries benchmark data for one of 8 critical minerals (copper, gold, silver, lithium, cobalt, nickel, manganese, graphite). Each response includes
  • Benchmark.Ultrasound: Returns attested field run logs for an ultrasound-assisted gravity-separation device (grooved stainless-steel tray). Each run includes feed parameters, ultrasound frequency, tray

What data it sees

Do you need an account

No: the server works without sign-in

Mineral intelligence API: 8 critical minerals (USGS benchmarks) with mineral processing and ultrasound run-log data. $0.10 USDC on Base via x402. Every response carries an on-chain EAS attestation.

How to connect

How to connect mineral-intel-benchmark to Claude

The server address to paste into Claude settings:

https://mineral-intel-benchmark--ntjson.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect mineral-intel-benchmark to ChatGPT

The server address to paste into ChatGPT settings:

https://mineral-intel-benchmark--ntjson.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect mineral-intel-benchmark to Cursor

The server address to paste into Cursor settings:

https://mineral-intel-benchmark--ntjson.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (6)

Raw names from tools/list. Only developers need these.

sales.askAsk anything about this API: what commodities are covered, how on-chain provenance works, pricing tiers, x402 payment flow, MCP integration, or the Extract API. Free to call. Returns a natural-language answer from a small LLM grounded on the API docs.
benchmark.commodityReturns USGS Mineral Commodity Summaries benchmark data for one of 8 critical minerals (copper, gold, silver, lithium, cobalt, nickel, manganese, graphite). Each response includes grade cutoffs, spot pricing, process-recovery benchmarks, production statistics, and an EAS attestation UID + IPFS CIDs anchoring the data on Base. Costs $0.10 USDC per call via x402 when invoked through the REST endpoint; this MCP tool surfaces the same data for discovery.
benchmark.ultrasoundReturns attested field run logs for an ultrasound-assisted gravity-separation device (grooved stainless-steel tray). Each run includes feed parameters, ultrasound frequency, tray geometry, gold recovery rates, and an EAS attestation UID anchoring the record on Base. Costs $0.10 USDC per call via x402 when invoked through the REST endpoint; this MCP tool surfaces the same data for discovery.
extract.estimateFree probe + price quote for paid structured-data extraction from a public document URL (pdf_digital, pdf_scanned, image, csv, txt). Returns estimate_id, source_type, page/row count, quality_floor grade (A/B/C/D), cost_breakdown {est_input_tokens, est_output_tokens, model_cost_usdc, margin_x, price_usdc}, and 15-min expires_at. Use the estimate_id with extract.run to pay via x402 USDC on Base. Honest grading: jobs returned as grade D receive an 80% auto-refund.
extract.runReturns invocation guidance for executing a paid extraction job after extract.estimate. Payment is x402 USDC on Base, amount equals cost_breakdown.price_usdc from the estimate (clamped onto the 5-tier ladder: $0.10 / $0.50 / $1.00 / $2.50 / $5.00). Result delivery: job_id + result + grade (A/B/C/D) + result_url. Grade D triggers 80% auto-refund. MCP cannot carry the X-PAYMENT header, so this tool returns the endpoint + price; execute the paid POST directly with an x402 client (x402-fetch, x402-axios).
extract.resultFetch the structured extraction result for a previously paid job. Returns job_id, grade (A/B/C/D), and the assay-extract-v0.1 result document (samples, doc_type, lab, report_date, OPSEC-rounded coords, raw_text). Requires the HMAC token from result_url. Result TTL is 24 h after the paid run completes.