Subgraph Registry

Agent-friendly semantic classification of all subgraphs on The Graph Network.

Pre-computed index of 14,700+ subgraphs with domain classification, protocol type detection, schema fingerprinting, canonical entity mapping, and composite reliability scoring.

What's new in 0.8.0 — three agent-discovery upgrades:

• Semantic search via 384-dim embeddings (semantic_search_subgraphs)
• Schema evolution tracking with stability days surfaced on every result (get_schema_changes)
• OpenAPI 3.1 spec auto-generated for MCP tools + REST routes, served at /.well-known/openapi.json

The Problem

Agents querying The Graph need to discover and select the right subgraph before they can query data. Today this requires 3-4 tool calls (search, check volumes, fetch schema, infer structure) before any real work happens. This registry flips that: agents start with structured knowledge, not a blank slate.

What It Does

1. Crawls all active subgraphs from the Graph Network meta-subgraph
2. Fetches the GraphQL schema for every deployment
3. Extracts contract addresses from each manifest's dataSources and templates — agents can answer "which subgraph indexes contract 0x… on chain X?"
4. Generates a per-subgraph starter GraphQL query from the parsed schema (real top entity, real fields, sensible orderBy) — no more generic boilerplate that doesn't compile against most subgraphs
5. Classifies each subgraph by domain, protocol type, canonical entities, and schema family
6. Scores reliability using on-chain signals (query fees, volume, curation, stake)
7. Returns x402 + legacy query URLs — agents can pay $0.01 USDC on Base per query (no API key) or use a Studio key
8. Publishes as SQLite database + REST API + MCP server + per-subgraph JSON-LD at /.well-known/subgraph/{id}.jsonld for ecosystem crawlers
9. Generates visual dashboards and bot-readable category files (auto-updated with each sync)

---

Querying with x402 (no API key)

Every result includes query_url_x402 alongside the legacy query_url. The Graph's public x402 gateway (live since 2026-05-08) accepts $0.01 USDC on Base per query with zero signup.

// An x402-native agent — discovery to data in two calls
const { recommendations } = await mcp.call("recommend_subgraph", {
  goal: "find DEX trades on Arbitrum",
});
const top = recommendations[0];

// POST your GraphQL query. The first call returns HTTP 402 with a
// base64 `payment-required` header; the x402 client signs the
// EIP-3009 USDC transfer on Base and retries automatically.
const data = await x402Fetch(top.query_url_x402, {
  method: "POST",
  body: JSON.stringify({ query: "{ swaps(first: 5) { id amountUSD } }" }),
});

Pricing manifest returned per subgraph:

{
  "amount_usd": 0.01,
  "asset": "USDC",
  "asset_contract": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
  "chain": "base",
  "network": "eip155:8453",
  "pay_to": "0x79DC34E41B2b591078d3dE222C43EcaaBD52FcCB",
  "scheme": "exact",
  "asset_transfer_method": "eip3009"
}

Client libraries: @graphprotocol/client-x402, x402-fetch, or any generic x402 wrapper.

---

Registry at a Glance

Charts auto-generated from registry.db on each sync. See python/generate_docs.py.

---

Browse by Category

Domains

Explore subgraphs by use case — each file lists the top 25 subgraphs ranked by reliability score.

Domain	Count	File
DeFi	11,218	Swaps, pools, lending, vaults, yield
NFTs	857	Collections, marketplaces, sales
Infrastructure	581	Indexers, oracles, registries
DAO	429	Governance, proposals, voting
Identity	401	ENS, name services, resolvers
Analytics	327	Snapshots, metrics, historical data
Gaming	247	Players, quests, items, worlds
Social	74	Profiles, posts, follows

Full index: docs/DOMAINS.md

Networks

Explore subgraphs by blockchain — each file lists the top 25 subgraphs on that chain.

Network	Count	File
Ethereum	2,377	Largest ecosystem
Base	1,728	Fast-growing L2
BSC	1,582	BNB Chain
Arbitrum	1,376	Leading L2
Polygon	1,266	Polygon PoS
Optimism	568	OP Stack L2
Avalanche	440	C-Chain

Full index: docs/NETWORKS.md

Protocol Types

Type	Count	Description
DEX	4,176	Uniswap, Sushi, Curve, Balancer, PancakeSwap
Lending	1,424	Aave, Compound, Morpho, Spark, Silo
Staking	867	Lido, Rocket Pool, EigenLayer, Graph Network
Bridge	771	Hop, Stargate, Across, Wormhole, LayerZero
NFT Marketplace	436	OpenSea, Blur, Rarible, Foundation
Governance	416	Snapshot, Tally, Compound Governor
Yield Aggregator	387	Yearn, Beefy, Harvest, Convex
Perpetuals	266	GMX, Gains, dYdX, Hyperliquid
Name Service	223	ENS, Space ID, Unstoppable Domains
Options	179	Premia, Dopex, Lyra, Hegic

---

Reliability Score

Each subgraph gets a composite reliability score (0-1) based on four on-chain signals:

Signal	Weight	What it measures
Query Fees	30%	GRT fees earned from actual usage
Query Volume	30%	30-day query count
Curation Signal	20%	GRT tokens curated by the community
Indexer Allocation	20%	GRT allocated to this subgraph by indexers

All values are log-scaled and capped at 1.0. A 0.5 penalty is applied if the subgraph has been denied/deprecated.

Score tiers: High (0.7+) = strong signal, real usage | Medium (0.3-0.7) = functional, some activity | Low (<0.3) = minimal signal or test deployment

---

MCP Server

The registry is available as an MCP server with dual transport — stdio for local clients and SSE/HTTP for remote agents.

The shipped server is the Node implementation in src/index.js; that's what npx subgraph-registry-mcp runs and what's published to npm. A Python equivalent in python/mcp_server.py is kept for local development against the same SQLite database — bug fixes and new tools should land in the Node version first.

6 tools:

• search_subgraphs — filter by domain, network, protocol type, entity, or keyword
• recommend_subgraph — natural language goal to best subgraphs (includes schema_stable_days)
• get_subgraph_detail — full classification for a specific subgraph (includes schema_changed_at)
• list_registry_stats — registry overview (domains, networks, counts)
• semantic_search_subgraphs — vector-similarity search over precomputed embeddings (sentence-transformers/all-MiniLM-L6-v2, 384-dim). Use for fuzzy/paraphrased goals where literal keyword match would miss.
• get_schema_changes — chronological schema-fingerprint history for a subgraph (one row per detected change). Helps agents prefer mature subgraphs whose data contract has been stable.

Install

# Claude Code
claude mcp add subgraph-registry -- npx subgraph-registry-mcp

# Claude Desktop
{
  "mcpServers": {
    "subgraph-registry": {
      "command": "npx",
      "args": ["subgraph-registry-mcp"]
    }
  }
}

# Remote agents (SSE)
npx subgraph-registry-mcp --http-only
# Then connect to http://localhost:3848/sse

The server auto-downloads the pre-built registry (8MB SQLite) from GitHub on first run.

---

Well-Known JSON-LD Manifest

Stable, machine-readable per-subgraph manifest that other crawlers and agent frameworks can index without going through MCP. Served by the Node MCP HTTP transport:

GET /.well-known/subgraph/{id}.jsonld     Full per-subgraph manifest (JSON-LD)
GET /subgraphs/{id}.jsonld                 Alias (same payload)
GET /.well-known/subgraph-index.jsonld     Discovery list — top 100 by reliability with @id links

Each manifest includes classification, parsed entities, contract addresses (from the indexed dataSources), endpoints (x402 + API-key), a per-subgraph starter query generated from the actual schema, pricing, and metadata. The @context + @type make the shape auto-discoverable.

# Start the HTTP transport
npx subgraph-registry-mcp --http-only

# Fetch the manifest for Uniswap V3 Mainnet
curl http://localhost:3848/.well-known/subgraph/5zvR82QoaXYFyDEKLZ9t6v9adgnptxYpKpSbxtgVENFV.jsonld

---

Semantic Search

Every subgraph has a precomputed 384-dim embedding from sentence-transformers/all-MiniLM-L6-v2, built from its display name, description, canonical entities, top schema entity names, and protocol metadata. At MCP-tool-call time the Node server embeds the query string with the same model (via @xenova/transformers, quantized ONNX bundled in the npm package — no first-call download) and ranks rows by cosine similarity.

const { subgraphs } = await mcp.call("semantic_search_subgraphs", {
  query: "lending positions near liquidation on a Layer 2",
  limit: 5,
});
// subgraphs[i].semantic_score is cosine similarity in [0, 1]; >0.5 ~= strong match.

Use it when:

• The goal is paraphrased or use-case-shaped (search_subgraphs is keyword-only).
• You're exploring "what data exists for X?" rather than fetching a specific protocol's subgraph.

Same model is shared between Python crawl-time (fastembed) and JS runtime (@xenova/transformers) — vectors are bitwise-comparable so cosine math gives consistent rankings across runtimes.

Embeddings add ~22 MB to registry.db (14k × 384 × 4 bytes); model bundle adds ~23 MB to the npm package.

---

Schema Evolution

Each crawl computes a schema_fingerprint (MD5 of sorted entity:field_count pairs) per subgraph. Whenever the fingerprint changes from the previous sync, an immutable row is written to schema_history. The table is append-only and survives full DB rebuilds.

const history = await mcp.call("get_schema_changes", {
  subgraph_id: "5zvR82QoaXYFyDEKLZ9t6v9adgnptxYpKpSbxtgVENFV",
});
// {
//   total_changes: 3,
//   stable_days: 47.2,
//   changed_within_24h: false,
//   changed_within_7d: false,
//   changes: [
//     { fingerprint: "abc123...", prev_fingerprint: "def456...", detected_at: 1717... },
//     ...
//   ]
// }

recommend_subgraph and get_subgraph_detail results now also include schema_changed_at (unix seconds of last detected change) and schema_stable_days so agents can prefer subgraphs whose data contract has been stable longer — useful when a query needs to keep working across the agent's planning horizon.

---

OpenAPI

The full API surface (MCP tools + REST routes) is published as OpenAPI 3.1:

• openapi.yaml — checked into the repo, single source of truth
• data/openapi.json — bundled with the npm tarball
• GET /.well-known/openapi.json — served by the HTTP transport for live discovery

The spec is regenerated on every release from the declarative TOOLS[] + REST_ROUTES[] exports in src/index.js via scripts/gen-openapi.js. CI fails any PR that touches src/index.js without regenerating the spec.

---

REST API

GET /summary                    Registry overview and stats
GET /domains                    Domain breakdown
GET /networks                   Network breakdown
GET /families                   Schema family groups (fork/clone detection)
GET /subgraphs                  Filter subgraphs
GET /subgraphs/{id}             Full detail for one subgraph (now includes contract_addresses and example_query)
GET /search?q=uniswap           Free-text search
GET /recommend?goal=...&chain=  Agent-optimized recommendation

# Start API server
cd python && python server.py

# Example: find DEX subgraphs on Arbitrum
curl "http://localhost:3847/recommend?goal=query+DEX+trades+on+Arbitrum&chain=arbitrum-one"

# Example: filter by entity type
curl "http://localhost:3847/subgraphs?entity=liquidity_pool&network=base&min_reliability=0.5"

---

Bot-Readable Category Files

The docs/ directory contains structured .md files with YAML frontmatter designed for AI agents and bots to consume:

docs/
├── DOMAINS.md           # Index of all domains with counts
├── NETWORKS.md          # Index of all networks with counts
├── charts/              # Auto-generated SVG visualizations
│   ├── domains.svg
│   ├── networks.svg
│   ├── protocol-types.svg
│   └── reliability.svg
├── domains/             # One file per domain
│   ├── defi.md          # Top 25 DeFi subgraphs by reliability
│   ├── nfts.md
│   ├── dao.md
│   └── ...
└── networks/            # One file per network
    ├── mainnet.md       # Top 25 Ethereum subgraphs by reliability
    ├── base.md
    ├── arbitrum-one.md
    └── ...

Each category file includes:

• YAML frontmatter (domain/network, count, percentage, last updated)
• Top 25 subgraphs ranked by reliability score
• MCP tool and REST API query examples

---

Architecture

Graph Network Subgraph (meta-subgraph, 140M queries/month)
    |
    v
crawler.py ---- async httpx, ID-based cursor pagination
    |
    v
classifier.py - rule-based domain/protocol classification + schema fingerprinting
    |
    v
registry.py --- builds SQLite + indices
    |
    ├── server.py ------ FastAPI REST API (:3847)
    ├── generate_docs.py SVG charts + category .md files
    └── scheduler.py --- weekly incremental sync

MCP Server (src/index.js, published to npm)
    ├── stdio   ←── Claude Desktop / Claude Code
    └── SSE     ←── OpenClaw / remote agents (:3848)

python/mcp_server.py — local-dev MCP server hitting the same SQLite DB

Quick Start (Local Build)

cd python
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

echo "GATEWAY_API_KEY=your-key-here" > .env

# Full crawl + classify (~11 min)
python registry.py

# Generate charts and category files
python generate_docs.py

# Start API server
python server.py

How It Stays Current

A GitHub Actions workflow runs every 3 days:

1. Incremental crawl (updatedAt_gte: lastSyncTimestamp)
2. Reclassify new/changed subgraphs
3. Regenerate SVG charts and category .md files
4. Commit and push updates

License

MIT