Using with AI

The fastest way to get an AI coding agent productive on a Pipes SDK project is to install the official Pipes SDK Agent Skill:

npx skills add subsquid-labs/skills/pipes-sdk

The skill activates automatically on tasks like “create an indexer for Uniswap V3 swaps” or “my indexer is syncing slowly, help me optimize it”. It covers scaffolding, runtime error diagnosis, sync tuning, and data-quality checks. Pair the skill with one or both MCP servers so the agent can read live data and look things up:

Portal MCP server: 31 tools for querying blocks, transactions, logs, instructions, and analytics across 110+ datasets.
Documentation MCP server — search and retrieve these docs from inside the agent.

If you’d rather feed docs into a model directly, the static llms.txt (index) and llms-full.txt (full content) files are kept in sync with the site. See the AI Development overview for the full menu.

Scaffolding with Pipes CLI

Pipes CLI and Pipes UI publish the 1.0 line under the npm beta tag, so the commands below pin @beta for those two packages. Without the pin, npm serves an older 1.0 alpha that does not accept the config shown here. @subsquid/pipes itself installs the 1.0 line by default, no tag needed.

In a few minutes, you’ll have a running pipe that indexes Orca Whirlpool swap instructions on Solana mainnet into a local PostgreSQL database.

Prerequisites

Node.js 22.15+
pnpm
Docker (for the bundled PostgreSQL container)

Initialize the project

Run the CLI in the directory where you want the project folder to land:

pnpx @subsquid/pipes-cli@beta init

The CLI prompts for the project folder name, package manager (please stick to pnpm for now), target database (ClickHouse or PostgreSQL), network type, default network, and one or more templates; each template then asks for its own parameters (e.g. contract deployments and block ranges). It then writes a runnable project and installs dependencies. You can supply a JSON config instead of filling the prompts manually. Here’s the configuration for Orca Whirlpool swap instructions mentioned above:

pnpx @subsquid/pipes-cli@beta init --config '{
  "projectFolder": "orca-example",
  "packageManager": "pnpm",
  "target": "postgresql",
  "networkType": "svm",
  "defaultNetwork": "solana-mainnet",
  "templates": [
    {
      "templateId": "custom",
      "params": {
        "contracts": [
          {
            "contractName": "OrcaWhirlpool",
            "contractEvents": [
              {
                "name": "swap",
                "type": "instruction",
                "inputs": [
                  { "name": "amount", "type": "u64" },
                  { "name": "sqrtPriceLimit", "type": "u128" }
                ]
              }
            ],
            "deployments": [
              {
                "address": "whirLbMiicVdio4qvUfM5KAg6Ct8VwpYzGff3uctyCc",
                "range": { "from": "latest" }
              }
            ]
          }
        ]
      }
    }
  ]
}'

--config also accepts a path to a JSON file. Each contract is described by one or more deployments (address + block range), and the root defaultNetwork applies to all of them. The config schema is published at cdn.subsquid.io/schemas/pipes_cli_config.json; to print it locally run

pnpx @subsquid/pipes-cli@beta init --schema

Whichever way you configure the project, the CLI saves the resolved config to pipes.config.json in the project folder. To change the generated code later, edit that file and re-run

pnpx @subsquid/pipes-cli@beta init --config <project-folder>/pipes.config.json

Re-running on an existing pipes project regenerates the code in place and preserves your .env.

Run the pipeline

The generated project includes a docker-compose.yml that brings up the target database and the pipeline together:

cd orca-example
docker compose --profile with-pipeline up

For an iterative dev loop, run the database in Docker and the pipeline locally:

docker compose up -d         # Postgres on :5432
pnpm run db:migrate          # apply the generated migration
pnpm run dev                 # tsx src/index.ts

Either way, rows start landing in the orca_whirlpool_swap table within a minute.

What was generated

The project layout:

orca-example

migrations

src

contracts

utils

index.ts

schemas.ts

.env

.gitignore

AGENTS.md

biome.json

docker-compose.yml

Dockerfile

drizzle.config.ts

package.json

pipes.config.json

pnpm-lock.yaml

pnpm-workspace.yaml

README.md

tsconfig.json

src/index.ts: the pipe, with its stream, decoder, and target.
src/schemas.ts: Drizzle table definitions.
src/contracts/: generated ABI bindings, one folder per program ID.
src/utils/index.ts: the enrichEvents helper that src/index.ts uses to turn decoded instructions into rows. It needs a one-line fix, described in the warning below.
migrations/: SQL migrations generated by drizzle-kit.
AGENTS.md: instructions for coding agents working on the project.
docker-compose.yml: Postgres and an optional pipeline service.
pipes.config.json: the resolved CLI config. Edit it and re-run init to regenerate the project.
.env: DB_CONNECTION_STR, which points at the local Postgres.

The pipe lives in src/index.ts. The decoder block defines what to extract + a light transform:

const custom = solanaInstructionDecoder({
  range: { from: 'latest' },
  programId: ['whirLbMiicVdio4qvUfM5KAg6Ct8VwpYzGff3uctyCc'],
  instructions: {
    swap: orcaWhirlpoolInstructions.swap,
  },
}).pipe(enrichEvents)

The decoder asks the Portal for swap instructions on the Orca Whirlpool program. enrichEvents (from src/utils/) reshapes each decoded instruction into a row matching the Drizzle table. See the Pipe anatomy and Handling instructions guides for more info on solanaInstructionDecoder(). The generated code passes programId, which still works but is deprecated since 1.0.0-beta.9. In new code, pass the program’s typegen module as program instead. See the decoder reference.

The generated src/utils/index.ts does not compile as-is: it reads v.blockNumber, a property DecodedInstruction no longer has. Change that line to blockNumber: v.block.number until the CLI template is fixed.

The main() function wires the decoder to a drizzleTarget:

export async function main() {
  await solanaPortalStream({
    id: '8babd3b7', // generated; keep it stable
    portal: 'https://portal.sqd.dev/datasets/solana-mainnet',
    outputs: { custom },
  }).pipeTo(
    drizzleTarget({
      db: drizzle(env.DB_CONNECTION_STR),
      tables: [orcaWhirlpoolSwapTable],
      onData: async ({ tx, data }) => {
        for (const values of chunkForInsert(data.custom.swap)) {
          await tx.insert(orcaWhirlpoolSwapTable).values(values)
        }
      },
    }),
  )
}

The id is a per-pipeline identifier (the CLI generates a random one). Keep it stable so the target’s cursor survives restarts. See Pipe anatomy for how the pieces fit together.

Other examples

Token balances

The tokenBalances template indexes pre/post token balances directly from blocks, with no program ID needed. The generated pipe uses solanaQuery() instead of an instruction decoder.

pnpx @subsquid/pipes-cli@beta init --config '{
  "projectFolder": "solana-tokens",
  "packageManager": "pnpm",
  "target": "postgresql",
  "networkType": "svm",
  "defaultNetwork": "solana-mainnet",
  "templates": [
    {
      "templateId": "tokenBalances"
    }
  ]
}'

The CLI has one built-in SVM template, tokenBalances, plus the open-ended custom template shown at the top of the page.

Pipes SDK

Squid SDK

Quickstart

Using with AI

Scaffolding with Pipes CLI

Prerequisites

Initialize the project

Run the pipeline

What was generated

Other examples

​Using with AI

​Scaffolding with Pipes CLI

​Prerequisites

​Initialize the project

​Run the pipeline

​What was generated

​Other examples

Using with AI

Scaffolding with Pipes CLI

Prerequisites

Initialize the project

Run the pipeline

What was generated

Other examples