How AI agents discover and use MCP servers in 2026 — discovery mechanisms, capability advertisement, and integration patterns. A practical guide for developers exposing DePIN data to autonomous agents via Model Context Protocol.
Of 800 cataloged DePIN networks, only 327 carry live data and 296 expose first-party supply telemetry. We examine the 339 networks with no free public feed, argue why explicit null-coverage bounds outperform modeled estimates, and introduce the not_covered map as an epistemic boundary layer for DePIN research.
A systematic comparison of 31 DePIN networks that expose public API endpoints for supply telemetry. Which networks serve first-party data, which require on-chain reads, and which have no public feed at all. Our catalog of 800 networks ranked by data accessibility.
DePIN token prices move fast, but valuation lives in the supply data underneath. We explain why circulating vs. total supply, utilization, and protocol fees matter more than the last price print — and how to source them verifiably.
In 2026 the DePIN vs. cloud cost debate is a data problem, not a vibes problem. We compare decentralized compute (Akash, io.net) and storage (Filecoin) against hyperscalers using verifiable supply and pricing data.
Not all DePIN networks generate revenue. We analyze on-chain protocol fees for 78 DePIN networks to show which ones have real economic activity and which are ghost towns. Revenue data sourced directly from chain state with verify_urls.
DePIN networks serve fundamentally different resource classes — storage, compute, GPU, bandwidth, wireless. We compare supply metrics across Filecoin, Akash, and io.net to show why cross-network comparison requires canonical metric mapping and why raw numbers mislead.
Most DePIN market cap figures are wrong because they multiply price by the wrong supply number. We break down circulating vs. fully-diluted valuation, how to source supply data directly, and why every number needs a verify_url.
DePIN is a transparency paradox: networks built on open ledgers still publish supply numbers nobody can verify. We diagnose the problem and lay out a concrete fix — verify_urls, canonical units, and Bitcoin-anchored provenance.
The headline GPU count on io.net is registered capacity, not working supply. We break down registered vs. active devices, explain why fill rate isn't utilization, and show how to query the real GPU supply data.
How anchoring DePIN telemetry batches to Bitcoin via OpenTimestamps creates a tamper-evident audit trail. Why this matters for data integrity, regulatory compliance, and building trust in decentralized infrastructure metrics.
Filecoin storage is measured in petabytes and exbibytes that get conflated constantly. We explain the unit trap (PB vs. EiB is a 1,024x error), how to read Filecoin's real storage stats, and why every value needs a unit and a verify_url.