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Subgraph Registry

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

Pre-computed index of 15,500+ 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 (subgraphs indexing subgraphs)

  2. Fetches the GraphQL schema for every deployment

  3. Classifies each subgraph by:

    • Domain: DeFi, NFTs, DAOs, Gaming, Identity, Infrastructure, Social, Analytics

    • Protocol Type: DEX, Lending, Bridge, Staking, Options, Perpetuals, Marketplace, etc.

    • Canonical Entities: Maps schema types to a standard vocabulary (Pool -> liquidity_pool, Swap -> trade, etc.)

    • Schema Family: Groups forks/clones by schema fingerprint

  4. Scores reliability (see Reliability Score below)

  5. Publishes as JSON registry + SQLite database + REST API

Quick Start

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

# Create .env with your Graph API key
echo "GATEWAY_API_KEY=your-key-here" > .env

# Full crawl + classify (all 15K+ subgraphs, ~11 min)
python registry.py

# Or limit to top N by signal
python registry.py --max 500

# Start API server
python server.py

API Endpoints

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

Example: Agent Recommendation

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

Returns the top subgraphs matching the intent, with reliability scores and query instructions.

Example: Filter by Entity Type

curl "http://localhost:3847/subgraphs?entity=liquidity_pool&network=base&min_reliability=0.5"

Weekly Sync

# Run weekly incremental updates (only fetches new/changed subgraphs)
python scheduler.py

# One-shot incremental
python scheduler.py --once

Architecture

Graph Network Subgraph (meta-subgraph, 140M queries/month)
    |
    v
crawler.py ---- async httpx, ID-based cursor pagination (bypasses 5K skip limit)
    |
    v
classifier.py - rule-based domain/protocol classification + schema fingerprinting
    |
    v
registry.py --- builds JSON registry + SQLite + indices
    |
    v
server.py ----- FastAPI REST API with /recommend endpoint
    |
    v
scheduler.py -- weekly incremental sync via updatedAt filtering

Output

File

Size

Description

registry.json

~130 MB

Full registry with all entity details

registry.db

~8 MB

SQLite with indexed lookups

sync-state.json

<1 KB

Last sync timestamp for incremental updates

Classification Results (as of March 2026)

Domain

Count

Network

Count

DeFi

11,841

Ethereum

2,471

NFTs

893

Base

1,845

Infrastructure

602

BSC

1,664

DAO

450

Arbitrum

1,442

Identity

424

Polygon

1,364

Analytics

348

Optimism

593

Gaming

255

Avalanche

454

Social

78

Reliability Score

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

Signal

Weight

What it measures

Source

Query Fees

30%

GRT fees earned from actual usage — proves real demand

Network subgraph

Query Volume

30%

30-day query count — recent activity level

QoS subgraph

Curation Signal

20%

GRT tokens curated — community vote of confidence

Network subgraph

Indexer Stake

20%

GRT staked by indexers — skin in the game

Network subgraph

All values are log-scaled and capped at 1.0. Usage signals (fees + volume) are weighted higher at 60% because they prove real demand. A 0.5 penalty is applied if the subgraph has been denied/deprecated.

What the scores mean:

  • 0.7–1.0: High reliability — strong signal, active indexers, real usage (e.g. Uniswap, Aave)

  • 0.3–0.7: Moderate — some signal and usage, likely functional

  • 0.0–0.3: Low — minimal signal, may be inactive or a test deployment

MCP Server

The registry is available as an MCP server for agent integration. It exposes 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 via NPM

npx subgraph-registry-mcp

Add to Claude Desktop

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

The server auto-downloads the pre-built registry (8MB SQLite) from GitHub on first run — no local build needed.

How It Stays Current

The Graph Network subgraph indexes all subgraph deployments on-chain. The crawler queries updatedAt_gte: lastSyncTimestamp to fetch only what changed since the last run. Weekly syncs keep the registry fresh without full rebuilds.

License

MIT

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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