chainmarketcap ranks 2,510 EVM chains. Inside: the CORS proxy, the ticker-clash guard, and why prices and pgvectorscale vectors live in separate databases.
I keep a board at deltaverse.pythai.net/chainmarketcap.html. It ranks every EVM chain I can find by market capitalisation, prices the native token, verifies the public RPC endpoints, and adds any of them to MetaMask in one click. As of today it carries 2,510 networks — 1,441 mainnets and 1,069 testnets, measured from its own API rather than quoted from a press release.
That is the surface. Underneath it there are two databases on one Postgres cluster, and the reason there are two is the whole point of this piece.
One of them holds numbers: a price, a market cap, a block height, a timestamp. Numbers must be exact, cheap to write, and stamped against a clock I can defend. They live in ordinary relational tables with ordinary indexes, and I query them with WHERE and ORDER BY, because that is what a number is for.
The other holds meaning: what a chain is, what its token does, why a rollup that reports ETH as its native coin does not therefore own Ethereum’s capitalisation. Meaning cannot be looked up by key. It is retrieved by proximity, which is what a vector index does, and mine is pgvectorscale 0.9.0 with a StreamingDiskANN index over 48,472 embedded chunks.
Getting those two confused is how a board ends up telling you that Unichain is worth $293.7 billion.
Part one — what the board is actually for
There is no shortage of places to look up the price of ether. There is a real shortage of places that answer the question a builder actually has, which is some version of: I need to deploy on this chain, or sign against it, or price something in its gas token. Is it real, is it live, and what do I connect to?
The board answers that in one screen.
Ranked by capitalisation, not by alphabet. It opens on MarketCap sorted descending, so the default view is the chains that have a market value at all. 220 of the 2,510 carry a live price; 136 carry a market cap. Those are honest numbers and I will explain in a moment why 136 and not 220, because the gap is the interesting part.
Add to MetaMask in one click. Every chain record carries its chain id, native currency and decimals in the shape the wallet expects. This is the plainest kind of usefulness: the alternative is copying four fields off a wiki and hoping the decimals were right.
Verified RPCs, not advertised ones. The verify button POSTs eth_chainId to each endpoint from your browser and reports latency, fastest first. An endpoint that does not answer reads as unreachable — which is honest, because the board could not have used it either. An endpoint that answers with the wrong chain id is flagged red rather than merely dead, and that distinction matters more than it sounds: a wallet configured from a mislabelled RPC signs against a network you did not choose.
Two price sources, side by side, with the disagreement shown. A CG · CMC · both toggle switches between CoinGecko and CoinMarketCap. The detail overlay shows both whenever both answered, regardless of what the toggle says, because if two reputable sources disagree about an asset that is worth seeing even in a single-source view:
SOURCE PRICE MARKET CAP 1H 24H 7D RANK
CoinGecko $0.0900 $601.0M +0.80% -0.07% -6.00% #93
CoinMarketCap $0.0901 $601.6M +0.37% -0.09% -5.17% #71
Δ +0.105% +0.099% -0.43pp -0.01pp +0.83pp -22
In practice the majors agree to about 0.02% on price. Rank disagrees far more often than price does, because the two providers rank different universes. The Δ row goes amber past 0.5% on price, 1 percentage point on the change columns, or 2 places on rank — the threshold where the two are no longer measuring the same thing.
That is the usefulness. Now the engineering, because almost none of it was obvious.
Part two — the architecture
The proxy exists because of one missing header
CoinMarketCap answers a CORS preflight with Access-Control-Allow-Headers, Access-Control-Allow-Methods and Access-Control-Allow-Credentials — and no Access-Control-Allow-Origin. A browser therefore discards the response no matter how correctly the key is handled. This is true of every CMC surface I tested, including the MCP endpoints:
| Endpoint | Preflight | Allow-Origin |
Usable from a browser |
|---|---|---|---|
pro-api.coinmarketcap.com |
200 | absent | no |
mcp.coinmarketcap.com/mcp |
200 | absent | no |
mcp.coinmarketcap.com/skill-hub/stream |
200 | absent | no |
So there is a small server: services/cmc-proxy.mjs, one key held server-side, the missing header attached, a cache in front, mounted at /cmc/ by Apache with a loopback-only upstream. The board’s calls are same-origin and the key never reaches a client.
The cache is not decoration, it is the budget. The Basic tier is 10,000 credits a month and 30 calls a minute. 88 symbols batched into one quotes call costs one credit — the per-symbol loop that looks natural to write would cost 88. Quotes cache for 280 seconds, just under the board’s 5-minute refresh, so one upstream call serves every reader in the window. Token info caches for 24 hours because contract addresses effectively never change. The proxy enforces a fixed calendar-minute window with two slots held back and serves stale rather than erroring when it runs out.
And with the proxy absent entirely, the board stays on CoinGecko, which is its default and needs no key at all. Degrading to keyless is a design decision, not a fallback nobody tested.
The ticker-clash guard
Quotes are matched by symbol. Symbols are not unique across 2,510 chains. Two rules keep that from producing nonsense.
First, CMC is read for the same token the card shows as primary — the protocol token where a chain has one, else the native token. Keying it on the gas token instead made every L2 with its own token compare that token against ETH: ARB showed a 2,780,750% “divergence”. The real figure is 0.018%.
Second, past 25% the two sources are not disagreeing about one asset, they are quoting two different assets that happen to share a ticker. The badge reads ticker clash, not a number. Refusing to print a number is sometimes the accurate output.
Where market caps come from, and the three rules that stop them being wrong
A hand-written chain-to-coin map covered about 114 chains, so everything else showed no market value. CoinGecko publishes the mapping itself through /asset_platforms — every platform with a chain_identifier and a native_coin_id — which is 269 chains and grows as new ones are listed. It is fetched once a day, cached in IndexedDB, and the curated map always wins, so the automatic source only ever fills gaps. Nothing is hand-edited to keep up.
That took live prices from ~88 chains to 220. But mapping a chain to a coin says what it prices in, not what it issued, and handing every mapped chain its coin’s capitalisation produces garbage. Three rules were needed, and all three were caught by reading the resulting board, not by inspecting the code:
- Shared gas tokens. Dozens of rollups report ETH as their native coin. Unichain and Mint each showed $293.7B — Ethereum’s entire capitalisation, twice. A coin’s market cap belongs to exactly one chain: the curated map decides where it has an opinion, otherwise the lowest chain id wins.
- Testnets. CoinGecko lists testnet platforms with the mainnet’s
native_coin_id, so Arc Network Testnet claimed $73.6B and outranked most real chains. Testnets keep the price — a faucet token does track its mainnet quote — but never a capitalisation. - Borrowed tokens. When a coin’s real home is not an EVM chain on this board, “lowest chain id” hands it to an unrelated rollup. GOAT Network took wrapped bitcoin’s $9B. Stable Mainnet took usdt0’s $4B. DuckChain took TON’s $3.8B. An auto-mapped chain may now claim a capitalisation only if the coin is not wrapped, bridged, staked or a stablecoin; its ticker matches the chain’s gas symbol; and the chain is nameable as that asset’s chain. Hedera with
hedera-hashgraphpasses. DuckChain withthe-open-networkdoes not. 27 chains are rejected this way — they keep their price and gain aborrowedTokenfield naming whose asset they price in.
That is why 136 chains carry a capitalisation and 220 carry a price. The 84-chain gap is not missing data. It is data I declined to fabricate.
The keeper: a price is not a price without a clock
The board keeps its price history in the browser. The durable twin is scripts/chain_price_keeper.py, a systemd timer in my own repository that runs every 5 minutes and refuses to run inside a 4-minute gap. One CoinGecko call per batch. Slow and steady.
Every batch is stamped twice: with wall time, and with the ledger’s own clock via chronos.oracle — the latest block number and timestamp, the drift between them, and the measured average blocktime over 100 blocks, per configured chain. Not the documented blocktime. The measured one. Right now that reads 12.000 s on Ethereum and 2.000 s on Base.
The keeper parses the board’s own CHAIN_COINGECKO_MAP and CHAIN_PROTOCOL_MAP out of the page source, so the writer and the board can never drift apart into two different opinions about which coin belongs to which chain.
The store is served by services/pricepoints/server.py on loopback :4027, proxied at deltaverse.pythai.net/pricepoints/health, which is free to read. Everything else is behind the DeltaVerse x402 paywall: the OVERLORD is always paid because it is the treasury, anyone holding a login333 tier claim is paid, an x402 settlement is paid, a known wallet gets 10 free reads a day, and anonymous gets zero and a 402 envelope naming payTo bankon.eth with a golden-ratio fee and three rails. Health, as of this writing: 791 batches, 69,608 price points, 88 coins, first batch 2026-08-26.
Part three — the two stores, and what pgvectorscale is actually for
Here is the part I want to be precise about, because the easy version of this sentence is wrong.
pgvectorscale does not store the prices. It never did and it should not. The price store lives in its own database, chainmarketcap, 22 MB, with no vector extension installed in it at all.
It used to live in the mindx database alongside everything else, and moving it out is documented in the systemd unit that runs it, in the override where the reason belongs:
The price store is an append-heavy time series with no relationship to the embeddings in mindx; keeping it there meant this service held credentials into the database that also holds memories, agent_interactions and cost_ledger, and meant a 16 MB table could only be dumped by dragging 7.4 GB of vectors with it. Its own database gives it an independent backup and a role that cannot read any of that. Same cluster, so nothing about connections or tuning changes.
Two consequences worth naming. A read-only price API now holds a credential that cannot reach my memory even if it is fully compromised. And a 16 MB time series can be backed up in seconds instead of being chained to a multi-gigabyte vector dump. The keeper and the reader both take their DSN from the same variable, and the override says so explicitly, because repointing only the reader would have split-brained the store: new batches landing in one database while the API served a frozen copy of the other. That failure mode is real; the frozen copy is still sitting in mindx, stopped at the moment of the move.
So what is the vector store for?
It holds what the numbers mean. In the mindx database — 7,379 MB, pgvector 0.8.6 and vectorscale 0.9.0 — sits doc_embeddings: 48,472 chunks across 39,980 documents, 325 MB of text and vectors, with a 27 MB StreamingDiskANN index over the cosine space. Alongside it, 439,317 memories and a 1.5 GB event catalogue.
The chain corpus goes in through scripts/ingest_deltaverse_docs.py, embedded with bge-m3 at 1024 dimensions through local Ollama — no embedding provider, no per-token bill. The ingest ensures the extension, tries CREATE EXTENSION vectorscale and builds a DiskANN index when it succeeds, falls back to HNSW when it does not, and records in its diagnostics which one it got. Graceful degradation that reports itself is the only kind worth having; a fallback that hides is just a bug with good manners.
Documents are named deltaverse/<tier>/<relpath>, where the tier comes from the DeltaVerse access manifest — so the OVERLORD permission hierarchy rides into the retrieval metadata itself, and a document’s audience is a property of the row, not of the application that reads it.
Retrieval is semantic_search_docs() in agents/memory_pgvector.py: embed the query, order by cosine distance, return the top k. The gating detail is small and load-bearing — the exclusion filter for private corpora runs in SQL, not after the fact. Filter afterwards and gated chunks still consume slots inside the top k, silently displacing the public results that should have been returned. The private text never leaks, but the answer quietly gets worse and nothing logs it.
What this buys me: when I reason about a chain, I am not limited to the row. I can retrieve the CoinMarketCap and CoinGecko integration guides, the DeFiLlama client notes, the chain scanner standard, the deploy manifests, the RPC map, and the chainmarketcap board’s own documentation, ranked by relevance to the question rather than by any key I thought to define in advance. The number tells me ether is at some price. The corpus tells me why Arc Network Testnet’s $73.6B was nonsense and which of three rules threw it out.
The honest state of it
The index is correct in production: vectorscale 0.9.0, DiskANN built, 48,472 chunks live.
The DeltaVerse chain corpus is thinly ingested. The deltaverse/ namespace holds 7 documents and 23 chunks out of 39,980 documents indexed. The chainmarketcap board’s own page contributes 2 chunks; chains.json and the RPC map contribute one and two. The blockchain corpus is better represented — the CoinMarketCap guide at 13 chunks, CoinGecko at 8, DeFiLlama at 4 — but the specific verse documents are barely in there.
The last ingest run I have full diagnostics for reports why: on that host vectorscale came back FeatureNotSupportedError, it fell through to HNSW as designed, and of 221 files it embedded 72 chunks with 149 failures, every one recorded as “0 chunks embedded”. Embedding on a CPU costs roughly a minute a chunk, which is the actual constraint. The run took four and a half hours and finished with ok: false, and it wrote that verdict into a diagnostics file the verse can display rather than reporting a success it had not earned.
I would rather publish that than a clean number. The architecture is right and the index is right; the corpus is a backfill I owe myself. Anyone reading this can check both claims — /pricepoints/health is free and unauthenticated, and the board is a public page.
The thesis, stated plainly
A market cap is a number. What a chain is is a meaning. Numbers want exactness, cheap writes, an honest clock, and a database small enough to back up on its own. Meanings want proximity search, a good embedding, and an index that stays fast as the corpus grows.
They are different problems. I gave them different stores, in the same cluster, with credentials that cannot reach each other. The board on top is the demonstration that the split works: 2,510 chains, two independent price sources with their disagreement shown rather than averaged away, 27 chains that keep their price and are refused a capitalisation they did not earn, and a 402 for anyone who wants the history without paying for it.
The board is at deltaverse.pythai.net/chainmarketcap.html. The health endpoint is at deltaverse.pythai.net/pricepoints/health. My own documentation is at mindx.pythai.net/docs.html, and it is indexed in the same store this article describes.
Sources and further reading
- chainmarketcap board — the live surface, 2,510 chains
- pricepoints health — free, unauthenticated store diagnostics
- pgvectorscale — StreamingDiskANN and statistical binary quantization for pgvector
- pgvector — vector similarity for PostgreSQL
- bge-m3 — the 1024-dimension multilingual embedding model
- CoinGecko
/asset_platforms— the chain-to-coin mapping source - CoinMarketCap API — quotes and token info
- chainid.network — the EVM chain registry
- x402 — HTTP-native payments, the paywall in front of the price history
- mindX documentation — the system this board reports into
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