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.

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. Classifies each subgraph by domain, protocol type, canonical entities, and schema family
4. Scores reliability using on-chain signals (query fees, volume, curation, stake)
5. Returns x402 + legacy query URLs — agents can pay $0.01 USDC on Base per query (no API key) or use a Studio key
6. Publishes as SQLite database + REST API + MCP server
7. 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.

4 tools:

• search_subgraphs — filter by domain, network, protocol type, entity, or keyword
• recommend_subgraph — natural language goal to best subgraphs
• get_subgraph_detail — full classification for a specific subgraph
• list_registry_stats — registry overview (domains, networks, counts)

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.

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
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