/data — the market data layer (Lane C)

Everything the agent can see. A pluggable source registry that merges partial contributions from any number of providers into one source-agnostic MarketSnapshot.

Nine sources ship today — GraphQL subgraphs, REST APIs, a contract read over JSON-RPC, and a prediction market. The registry is the product; they are its consumers.

---

Purpose

The agent decides where to put capital, so what it can see determines what it can do. This layer owns that, with two goals held simultaneously:

1. Win three Graph tracks now — live Messari standardized subgraphs, the Token API, a standalone MCP server, and x402 pay-per-query.
2. Make adding a non-Graph provider later a 30-minute job — Chainlink, Pyth, DefiLlama.

Those goals conflict only if the Graph adapters drive the design. They don't: the registry and the MarketSnapshot shape came first, and no provider name appears anywhere above sources/ (asserted by tests/test_source_agnostic.py).

---

Public interface

The one call Lane B needs

from curator_data import build_registry

registry = build_registry()                              # reads .env
snapshot = await registry.snapshot(
    mandate.permitted_data_sources,                      # ["messari", "token_api"]
    mandate.constraints.allowed_assets,                  # ["USDC", "WETH"]
)

Implements the frozen DataSourceRegistry port. Returns a MarketSnapshot.

Method	Returns	Notes
await registry.snapshot(source_keys, assets)	MarketSnapshot	Fans out concurrently, merges, never raises for source failure
registry.available()	list[str]	Registered keys — the set the genesis UI offers
registry.describe()	list[dict]	Key, human description and capabilities, for a source picker
registry.sources_providing(*kinds)	list[str]	Capability lookup: who supplies "price"?
registry.register(key, factory)	None	Runtime registration, for embedders and tests
await registry.aclose()	None	Releases every source's HTTP client. Also an async context manager

For late-binding consumers (Lane B)

The agent harness resolves its data seam from configuration rather than importing this lane directly, so it needs an instance at a stable path. That is:

AGENT_DATA_REGISTRY=curator_data.default:registry

curator_data/default.py exposes a ready-made Registry built from the environment. It satisfies the frozen DataSourceRegistry Protocol, and importing it cannot fail on a missing GRAPH_API_KEY — sources are constructed lazily, so an absent credential degrades into snapshot.errors rather than raising at import and dropping the caller back to fixtures.

Market-level views

MarketSnapshot is a flat fact list, which is what keeps it source-agnostic — but that is not how you render a table. Pivot it:

from curator_data.queries import pivot_markets, pivot_pools, prices, errors_as_dicts

for row in pivot_markets(snapshot):        # sorted by APY, highest first
    print(row.protocol, row.supply_apy, row.tvl_usd, row.utilization, row.fact_ids)

MarketRow / PoolRow both expose .to_dict(). row.fact_ids is what belongs in AllocationDecision.facts_used.

Command line

uv run curator-data sources          # what a mandate may grant
uv run curator-data protocols        # what is configured, and how to add more
uv run curator-data snapshot --assets USDC,WETH [--json]
uv run curator-data verify-live      # prove the demo path hits live data (exit 1 if not)

snapshot --json emits a schema-valid MarketSnapshot on stdout, so another lane can consume real data without importing any of this.

---

Data shapes

Everything crossing the boundary is defined in packages/schema. Nothing new is invented here.

{
  "taken_at": "2026-07-25T14:05:00Z",
  "facts": [
    {
      "id": "messari:yield:aave-v3/usdc",   // stable across snapshots; cite this
      "kind": "yield",                       // yield|price|tvl|liquidity|volatility|utilization|volume
      "subject": { "protocol": "aave-v3", "market": "USDC", "chain": "base" },
      "value": 0.0432,                       // 4.32% — a FRACTION, never 4.32
      "unit": "apy_fraction",
      "source": "messari",                   // provenance — the UI shows this
      "observed_at": "2026-07-25T14:04:12Z"
    }
  ],
  "errors": [ { "source": "moonwell", "message": "HTTP 502" } ]
}

errors is not decoration. A non-empty errors means the snapshot is partial. Show it to the model — an agent that treats a partial view as complete is the failure mode this layer is shaped to avoid, and it holds a key.

---

Sources that ship

Key	Provides	Data	Live status
messari	yield, tvl, utilization, liquidity	Messari standardized subgraphs — lending markets and DEX pools on Base	✅ Moonwell verified live (~15% USDC APY on $14.5M). Uniswap V3 works but its indexers are slow/intermittent
aave	yield, tvl, utilization	Aave V3 on Base, via Aave's own subgraph schema	✅ verified live (3.41% USDC APY on $174.9M, 0.84 utilization)
chainlink	price	Chainlink feeds, read on-chain over JSON-RPC	✅ verified live (WETH $1,858.98, USDC $0.9999). Needs no credential
token_api	price	The Graph Token API — prices derived from executed DEX swaps	✅ verified live (WETH $1,857.95). Needs its own Graph Market JWT, not GRAPH_API_KEY
defillama	yield, tvl	Every Base pool DefiLlama tracks, in one unauthenticated call	✅ verified live — 47 facts across ~20 protocols. No credential
feargreed	sentiment	Crypto Fear & Greed index, normalised to 0–1	✅ verified live (0.27 — "Fear"). No credential
gas	gas	Base gas price and the USD cost of one rebalance, read on-chain	✅ verified live ($0.74 per rebalance at 1 gwei). No credential
morpho	yield, tvl, utilization	Morpho Blue markets on Base, via Morpho's own API	✅ verified live — 15 markets, USDC/cbBTC at 4.80% on $1.42bn. No credential
prediction	probability	Polymarket implied probabilities on rates, inflation and crypto	✅ verified live (75.2% no change in Fed rates). No credential, read-only

All subgraph IDs live in curator_data/sources/protocols.py, including a list of candidates rejected after live testing, so nobody re-adds them.

The only forward-looking source

Every other source reports what already happened — an APY is what a market paid, TVL is what is there now. prediction reports what people expect, priced by people with money on it. For a book made of lending yield, a 24% implied chance of a rate rise is information no APY series contains.

Six sources need no credential, and that is the point

Before them, every registered source needed a Graph key: a fresh clone produced an empty snapshot and four error lines. defillama, feargreed, gas, chainlink, morpho and prediction need none, so cloning the repo and running curator-data snapshot returns real data in one command.

DefiLlama is breadth. The Graph is depth. Do not confuse them

The subgraph sources stay the sources of record: queried per-protocol against indexed chain state, verifiable, and what the Graph integration actually is. DefiLlama is a third-party aggregator reporting numbers it computed from someone else's data, so its facts carry a lower Fact.confidence and the curator prompt prefers a subgraph where the two disagree.

What it buys is a real gap closed. Before it, the agent compared Aave against Moonwell and we called that a multi-protocol comparison. Two protocols is not a market.

Yields are apyBase, never the headline. The first live run put aerodrome-slipstream USDC-CBBTC at 91.14% above aave-v3 USDC at 3.50%, and an agent told to pursue yield would read that as Aave being 26× worse. It is not: 91% was apyBase + apyReward, and the reward leg is a token emission — a bet on the emitted token's price, with a different risk profile and an expiry date, not interest. The base figure was 14.66%. Where DefiLlama publishes no split, the headline is used and a MarketSnapshot.notes entry says so.

sentiment and gas are new Fact.kinds, not overloaded old ones

_KIND_LABELS in the curator prompt exists because a 3B model once read f6 | liquidity | $12.4M as "the highest headline APY of 10.43%". A utilization of 0.78 and a sentiment of 0.78 mean entirely different things, so they get different kinds and render differently. Extending the enum is what the schema comment asks for; overloading a kind is how that misread happens again.

gas closes a blind spot with real consequences: the agent could see a 3 bps yield edge and had no way to know that capturing it costs more than it earns.

Two independent price sources, on purpose

chainlink reads an oracle; token_api derives price from executed DEX swaps. The mechanisms share nothing, so agreement corroborates and disagreement is a signal — a stale oracle, a manipulated pool, or a genuinely dislocated market. Live they sat 0.19% apart.

prices(snapshot) therefore returns every observation rather than one winner:

{"WETH": {"price_usd": 1857.18,          # median consensus
          "sources": ["chainlink", "token_api"],
          "observations": [{"source": "chainlink", "price_usd": 1858.98, ...}, ...],
          "spread_pct": 0.19, "disagreement": False}}

chainlink also reads the same feeds totalAssets() uses, so the agent and the vault contract can never disagree about what the portfolio is worth.

Why Aave is a separate source rather than a branch in messari

Live introspection showed the published Aave V3 Base subgraph exposes reserves, not the standardized markets — so one query shape genuinely cannot read it. It could have been a second query inside the Messari adapter, but Fact.source is provenance: labelling data pulled from Aave's own subgraph as messari would be false to anyone reading the dApp.

Adding it was sources/aave.py plus one line in sources/__init__.py. Nothing else changed — not the registry, the schema, the MCP server or the agent. That is the extension-point claim exercised on a real provider rather than a test double.

---

Adding a data source

The extension point. One new file, one new line.

# curator_data/sources/pyth.py
from curator_data.ports import BaseSource
from curator_data.facts import FactBuilder

class PythSource(BaseSource):
    key = "pyth"
    provides = ("price",)
    description = "Pyth price feeds on Base"

    async def fetch(self, assets):
        builder = FactBuilder(self.key)
        return [builder.usd("price", builder.subject(token=a), await self._read(a))
                for a in assets]

def make_pyth_source(settings):
    return PythSource(settings)

# curator_data/sources/__init__.py — the ONLY other edit
SOURCE_FACTORIES = {
    "messari": make_messari_source,
    "token_api": make_token_api_source,
    "aave": make_aave_source,
    "chainlink": make_chainlink_source,
    "pyth": make_pyth_source,                # ← this line
}

Then name "pyth" in a mandate's permitted_data_sources. Nothing else changes — not the registry, not the schema, not the agent, not the dApp. Because sources are selected by capability (provides), the new source immediately participates in price queries and in the MCP server's get_token_price — and it is cross-checked against the existing price sources for free.

This is not a hypothetical. aave and chainlink were both added this way after the registry shipped, and chainlink is not even an HTTP API — it reads a contract over JSON-RPC. Neither required a change outside its own file plus one line here.

Adding a protocol to an existing source is even smaller — one Protocol(...) line in protocols.py. That is the point of Messari standardized subgraphs: every lending market answers the same GraphQL document, so a new protocol needs no adapter at all.

What a source must guarantee

• Never raise for expected failure — a timeout, a rate limit, a missing market. Return what you have and call self.note("...") for the rest; notes surface in snapshot.errors.
• Normalise at the boundary. apy_fraction is 0.0432 for 4.32%. Use FactBuilder.apy_from_percent() when the upstream reports percentages — Messari does.
• Never guess an identifier. An unknown token symbol is a note naming the fix, not a guessed contract address. This system trades with a real key.

---

Dependencies

Requires: curator-schema (the frozen interface), httpx, pydantic, python-dotenv. Optional: eth-account for x402 (pip install curator-data[x402]).

Depends on no other lane. Lane B consumes this through the DataSourceRegistry port; nothing here imports agent/, venues/, web/ or contracts/.

Credentials

Variable	Required	Default	Purpose
GRAPH_API_KEY	yes	—	Subgraph gateway. Free at thegraph.com/studio → API Keys
TOKEN_API_KEY	no	falls back to GRAPH_API_KEY	Token API bearer token — a separate credential
TOKEN_API_URL	no	https://api.pinax.network/v1	⚠️ not token-api.thegraph.com — that host, named in The Graph's own docs, does not resolve. Verified live
DATA_CHAIN	no	base	Chain to query
DATA_REQUEST_TIMEOUT_S	no	15	Per-HTTP-request timeout
DATA_SOURCE_TIMEOUT_S	no	20	Per-source ceiling inside snapshot()
X402_ENABLED	no	false	Pay-per-query. Needs X402_PRIVATE_KEY too
X402_PRIVATE_KEY	no	—	Wallet with a few dollars of USDC on Base

---

The MCP server

curator_mcp/ is a separate distribution, published on PyPI — its own pyproject.toml, README.md and SKILL.md. No clone required:

uvx curator-mcp

{ "mcpServers": { "curator": { "command": "uvx", "args": ["curator-mcp"],
                               "env": { "GRAPH_API_KEY": "..." } } } }

Verified from a machine that has never seen this repo. Release process: PUBLISHING.md · ./publish.sh.

Tools: compare_protocols, get_market_yields, list_markets, get_token_price.

It shares this package's sources rather than reimplementing them, so the reusable product runs the same code as our demo. Our agent talks to the registry directly (in-process, no stdio hop) — it is visibly a consumer, not the consumer.

---

x402 — pay-per-query

Off by default. Enabled only by X402_ENABLED=true and X402_PRIVATE_KEY.

It is a decorator over the gateway transport, not a data source:

GatewayClient         API-key auth. Always works. The default.
X402GatewayClient     wraps it. Tries to pay; delegates on ANY failure.

There is no code path where enabling x402 loses data the API-key path would have returned. Worst case is a wasted round-trip and a note in errors. A client-side ceiling refuses to sign anything above 1 USDC — a market-data query costs a fraction of a cent, so a larger demand means something is wrong.

---

Assumptions & invariants

Callers may rely on all of these:

• snapshot() never raises for source failure, timeout or an unknown source key. Those degrade into errors[]. It raises only for programmer error.
• Every Fact.source is the registry key that produced it. Enforced at merge; a mislabelled fact is corrected and reported.
• Fact ids are unique within a snapshot and stable across snapshots for the same subject, so facts_used citations are unambiguous and decisions can be diffed over time.
• APY is always a fraction. 0.0432 means 4.32%.
• Amounts in USD are floats; no uint256 crosses this boundary — this layer reports market observations, not balances.
• A source is constructed once and reused across ticks, so connection pools survive. Call aclose() when finished.
• permitted_data_sources is access control. A registered source not named is never consulted.

---

Tests

uv run pytest data/tests -q          # 180 tests, no network, no credentials
uv run curator-data verify-live      # the live path — needs GRAPH_API_KEY

The unit suite never touches the network (httpx.MockTransport); verify-live only touches the network. Live gateway data on the demo path is a Graph submission gate, so it is a command rather than an assumption.

tests/conftest.py strips credentials and disables .env discovery for every test. That is deliberate: when a real GRAPH_API_KEY first landed in .env, three tests changed behaviour and several others silently began making live calls. The suite now asserts the same thing on a laptop with a full .env and on a fresh clone with none — which is what the macOS handoff needs.

⚠️ Shared-venv trap. uv sync --extra data prunes every package not in the named extras, which silently uninstalls other lanes' dependencies. Always sync all of them: uv sync --extra dev --extra data --extra agent --extra venues.

---

Layout

curator_data/
  config.py         Settings — every env value resolved in one place
  ports.py          BaseSource: the class a new source subclasses
  facts.py          FactBuilder — unit-safe, provenance-stamped Fact construction
  registry.py       fan-out, merge, degradation, capability lookup  ← the extension point
  queries.py        pivots from flat facts back into market rows
  verify.py         live-path checks (importable; the CLI just prints them)
  cli.py            curator-data: sources / protocols / snapshot / verify-live
  graph/            gateway transport (GraphQL over httpx) + transport factory
  sources/
    __init__.py     THE REGISTRATION TABLE — one line per source
    protocols.py    protocol -> subgraph id      (data, not code)
    tokens.py       symbol -> contract address   (data, not code)
    messari.py      Messari standardized subgraphs
    token_api.py    Graph Token API
  x402/             pay-per-query transport decorator, feature-flagged
curator_mcp/        SEPARATE DISTRIBUTION — the standalone MCP server
tests/

Plan: plans/2026-07-25-lane-c-data.md. Decisions and their reasoning: docs/build-log.md.