Effect RPC

The HTTP API guide showed how to build REST-style endpoints with schema validation. Effect RPC takes a different angle — you define procedures instead of HTTP endpoints, and you get a fully typed client for free with no URL construction or manual serialization.

The transport is still HTTP under the hood, and both patterns produce the same HttpEffect type, so the wiring story is identical to the HTTP API guide:

1. Define schemas outside. Domain types and tagged errors, importable by both server and client.
2. Construct the service inside the Worker’s Init phase. RpcGroup.toLayer is pure construction — safe to call at plan time. Don’t yield* the running server; it can’t run without a request.
3. Return { fetch } where fetch is the HttpEffect produced by RpcServer.toHttpEffect.
4. Bonus: deploy and call the procedures from a typed client that shares the exact same RpcGroup value.

1. Define the schemas

Domain model and error types — pure schemas, no runtime concerns:

src/task.ts

import * as Schema from "effect/Schema";

export class Task extends Schema.Class<Task>("Task")({
  id: Schema.String,
  title: Schema.String,
  completed: Schema.Boolean,
}) {}

export class TaskNotFound extends Schema.TaggedClass<TaskNotFound>()(
  "TaskNotFound",
  { id: Schema.String },
) {}

export class CreateTaskFailed extends Schema.TaggedClass<CreateTaskFailed>()(
  "CreateTaskFailed",
  { message: Schema.String },
) {}

RPC errors are schema-backed tagged classes. The client receives them as typed values you can match on — not raw HTTP status codes.

2. Declare the RPCs

Each Rpc.make declares one procedure: a name, a payload schema, a success schema, and an error schema. RpcGroup.make collects them into a single value that both the server and the client will share.

src/rpcs.ts

import * as Schema from "effect/Schema";
import { Rpc, RpcGroup } from "effect/unstable/rpc";
import { Task, TaskNotFound, CreateTaskFailed } from "./task.ts";

const getTask = Rpc.make("getTask", {
  success: Task,
  error: TaskNotFound,
  payload: { id: Schema.String },
});

const createTask = Rpc.make("createTask", {
  success: Task,
  error: CreateTaskFailed,
  payload: { title: Schema.String },
});

export class TaskRpcs extends RpcGroup.make(getTask, createTask) {}

TaskRpcs is just a value-level description. Nothing executes yet.

3. Build the Worker

Create src/worker.ts with an empty Init phase:

src/worker.ts

import * as Cloudflare from "alchemy/Cloudflare";
import * as Effect from "effect/Effect";

export default Cloudflare.Worker(
  "Worker",
  { main: import.meta.path },
  Effect.gen(function* () {
    return {};
  }),
);

The generator inside Cloudflare.Worker is the Init phase — it runs both at plan time and at runtime. Only do pure construction or resource-binding factories here; never yield* work that needs an incoming request.

3a. Bind an R2 bucket for storage

Tasks need durable storage. Declare an R2Bucket resource and bind it inside Init — bind() returns a typed handle whose get / put / delete / list methods we’ll call from the handlers below.

src/bucket.ts

import * as Cloudflare from "alchemy/Cloudflare";

export const Tasks = Cloudflare.R2Bucket("Tasks");

import { Tasks } from "./bucket.ts";

export default Cloudflare.Worker(
  "Worker",
  { main: import.meta.path },
  Effect.gen(function* () {
    const tasks = yield* Cloudflare.R2Bucket.bind(Tasks);

    return {};
  }),
);

We’ll provide the runtime side of this binding (Cloudflare.R2BucketBindingLive) in step 3c when we wire up the fetch handler.

3b. Construct the handlers inside Init

TaskRpcs.toLayer takes an Effect that returns one handler per procedure and produces a Layer. Like HttpApiBuilder.group, this is pure construction — it builds a value, it doesn’t run the server.

Don’t yield* TaskRpcs.toLayer(...) here. Building a layer is fine, but actually executing the procedures requires an incoming request. Init only constructs; the work happens later, on each fetch call.

  Effect.gen(function* () {
    const tasks = yield* Cloudflare.R2Bucket.bind(Tasks);

    const handlersLayer = TaskRpcs.toLayer({
      getTask: ({ id }) =>
        Effect.gen(function* () {
          const object = yield* tasks.get(id);
          if (!object) {
            return yield* Effect.fail(new TaskNotFound({ id }));
          }
          return Schema.decodeUnknownSync(Task)(JSON.parse(yield* object.text()));
        }).pipe(Effect.orDie),
      createTask: ({ title }) =>
        Effect.gen(function* () {
          const task = new Task({
            id: crypto.randomUUID(),
            title,
            completed: false,
          });
          yield* tasks.put(task.id, JSON.stringify(task));
          return task;
        }).pipe(
          Effect.catchTag("R2Error", (error) =>
            Effect.fail(new CreateTaskFailed({ message: error.message })),
          ),
        ),
    });

    return {};
  }),

Each handler receives the typed payload and returns an Effect that either succeeds with the declared success schema or fails with the declared error schema. getTask uses Effect.orDie to turn unexpected R2 failures into 500s — TaskNotFound is the only client-visible error. createTask maps R2 failures into the declared CreateTaskFailed error so the client can match on it.

3c. Return { fetch }

RpcServer.toHttpEffect converts the RpcGroup into an HttpEffect — exactly the type Workers expect for fetch. We provide two layers to it:

• The handlersLayer we just built.
• RpcSerialization.layerJson — tells the server to encode and decode messages as JSON. (Swap for layerNdjson, layerMsgPack, etc. as needed.)

Unlike the HTTP API approach, RPC doesn’t need HttpPlatform.layer or Etag.layer — the RPC server handles message framing internally.

    return {
      fetch: RpcServer.toHttpEffect(TaskRpcs).pipe(
        Effect.provide(handlersLayer),
        Effect.provide(RpcSerialization.layerJson),
      ),
    };

Putting it together

src/worker.ts

import * as Cloudflare from "alchemy/Cloudflare";
import * as Effect from "effect/Effect";
import * as Schema from "effect/Schema";
import { RpcSerialization, RpcServer } from "effect/unstable/rpc";
import { Tasks } from "./bucket.ts";
import { CreateTaskFailed, Task, TaskNotFound } from "./task.ts";
import { TaskRpcs } from "./rpcs.ts";

export default Cloudflare.Worker(
  "Worker",
  { main: import.meta.path },
  Effect.gen(function* () {
    const tasks = yield* Cloudflare.R2Bucket.bind(Tasks);

    const handlersLayer = TaskRpcs.toLayer({
      getTask: ({ id }) =>
        Effect.gen(function* () {
          const object = yield* tasks.get(id);
          if (!object) {
            return yield* Effect.fail(new TaskNotFound({ id }));
          }
          return Schema.decodeUnknownSync(Task)(
            JSON.parse(yield* object.text()),
          );
        }).pipe(Effect.orDie),
      createTask: ({ title }) =>
        Effect.gen(function* () {
          const task = new Task({
            id: crypto.randomUUID(),
            title,
            completed: false,
          });
          yield* tasks.put(task.id, JSON.stringify(task));
          return task;
        }).pipe(
          Effect.catchTag("R2Error", (error) =>
            Effect.fail(new CreateTaskFailed({ message: error.message })),
          ),
        ),
    });

    return {
      fetch: RpcServer.toHttpEffect(TaskRpcs).pipe(
        Effect.provide(handlersLayer),
        Effect.provide(RpcSerialization.layerJson),
      ),
    };
  }).pipe(Effect.provide(Cloudflare.R2BucketBindingLive)),
);

4. Add to the Stack

alchemy.run.ts

import * as Alchemy from "alchemy";
import * as Cloudflare from "alchemy/Cloudflare";
import * as Effect from "effect/Effect";
import Worker from "./src/worker.ts";

export default Alchemy.Stack(
  "TaskRpc",
  { providers: Cloudflare.providers() },
  Effect.gen(function* () {
    const worker = yield* Worker;
    return { url: worker.url };
  }),
);

5. Deploy

alchemy deploy

Bonus: call it from a typed client

Because TaskRpcs is just a value, the same group drives a fully typed client — no codegen. client.createTask accepts { title: string } and returns Effect<Task, CreateTaskFailed>.

scripts/client.ts

import * as Effect from "effect/Effect";
import * as HttpClient from "effect/unstable/http/HttpClient";
import { FetchHttpClient } from "effect/unstable/http/FetchHttpClient";
import { RpcClient, RpcSerialization } from "effect/unstable/rpc";
import { TaskRpcs } from "../src/rpcs.ts";

const program = Effect.gen(function* () {
  const client = yield* RpcClient.make(TaskRpcs);

  const task = yield* client.createTask({ title: "Write docs" });
  console.log("Created:", task.id);

  const fetched = yield* client.getTask({ id: task.id });
  console.log("Fetched:", fetched.title);
});

Effect.runPromise(
  program.pipe(
    Effect.provide(
      RpcClient.layerProtocolHttp({
        url: process.env.TASK_RPC_URL!,
      }),
    ),
    Effect.provide(RpcSerialization.layerJson),
    Effect.provide(FetchHttpClient.layer),
  ),
);

Get the URL from the deploy output and run it:

TASK_RPC_URL=https://your-worker.workers.dev bun scripts/client.ts

The errors are typed values: client.getTask returns Effect<Task, TaskNotFound>, and you can Effect.catchTag( "TaskNotFound", ...) to handle the missing case explicitly.

HTTP API vs RPC

Both approaches produce the same HttpEffect and wire into a Worker the same way. The difference is in how clients interact:

• HTTP API — standard REST endpoints, any HTTP client can call them. Best for public APIs.
• RPC — typed procedures, ideal for service-to-service communication where both sides share the schema definitions.

You can even combine them in the same Worker — serve an HTTP API for external consumers and RPC for internal services.

Recap

• Schemas (Task, TaskNotFound, CreateTaskFailed) and the RPC group (TaskRpcs) live outside the Worker — pure descriptions, importable by clients.
• The handlers are constructed inside the Worker’s Init phase closure via TaskRpcs.toLayer. We build a Layer but never yield* the running server.
• The Worker’s surface is { fetch }, where fetch is the HttpEffect produced by RpcServer.toHttpEffect.
• The same TaskRpcs value drives a fully typed client via RpcClient.make, with errors as typed values rather than HTTP status codes.