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. Publishes as SQLite database + REST API + MCP server
6. Generates visual dashboards and bot-readable category files (auto-updated with each sync)

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Registry at a Glance

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

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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

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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

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MCP Server

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

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.

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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"

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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

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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)
    ├── stdio   ←── Claude Desktop / Claude Code
    └── SSE     ←── OpenClaw / remote agents (:3848)

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