Compare
gRPC vs. Graftcode

Same wire speed. Far less code.

Skip the .proto files, the stub regeneration, the status-code mapping. Expose a class and call it.

[T]TRY IT FREE [F]FULL COMPARISON

/USED BY LEADING COMPANIES

/AT GLANCE

gRPC vs Graftcode

Both give you strong typing and fast calls. The difference is everything around the call.

Write and share a .proto contract for every service
Regenerate stubs by hand whenever the interface changes
Implement a generated service interface, not a plain class
Map exceptions to gRPC status codes on both sides
You are limited to remote only

Expose an ordinary public class — zero annotations, no IDL
The typed Graft auto-refreshes when your interface evolves
Install the Graft like any npm / NuGet / pip package
Normal exceptions propagate — no status-code mapping
In-process ↔ remote is a config switch, not a rewrite

/WHY SWITCH

Three reasons teams move from gRPC

gRPC solved fast RPC. It didn't remove the work that surrounds every call.

getUser call skipping .proto files on the way to Graftcode

No .proto, no stubs

Graftcode reads your public method signatures directly. There's no contract file to author, distribute, or keep in sync — and no protoc step to run on every change.

In-process and remote topology switched in configuration

Topology is configuration

Move a module from in-process to remote, or swap the transport, without touching a single caller. gRPC bakes the wire into your code; Graftcode keeps it out of it.

AI-ready out of the box

Your public methods are exposed as MCP tools automatically. Any MCP client — Claude, Cursor, ChatGPT — calls them as-is. With gRPC that's a custom wrapper you write and maintain.

[F]FULL COMPARISON

/SHOW, DON'T TELL

Same call. 4 steps vs 2.

A single typed remote call — getUser(42) — end to end.

gRPC

write the .proto

service UserService {
  rpc GetUser (GetUserRequest) returns (User);
}
message GetUserRequest { int32 id = 1; }
message User { int32 id=1; string name=2; }

regenerate stubs

$ protoc --go_out=. --go-grpc_out=. user.proto

implement + map DTOs

func (s *server) GetUser(ctx, r *pb.GetUserRequest)
    (*pb.User, error) {
  u := db.Find(r.Id)
  return &pb.User{Id:u.Id, Name:u.Name}, nil
}

dial, build stub, call

conn, _ := grpc.Dial(addr, opts...)
client := pb.NewUserServiceClient(conn)
res, err := client.GetUser(ctx, &pb.GetUserRequest{Id:42})

GRAFTCODE

expose a class

export class BillingService {
  calculateBill(kwhUsed: number): number {
    return kwhUsed * 0.42;
  }
}

Install the Graft & call

import { BillingService } from "@acme/billing-service";

const billing = new BillingService();

const total = billing.calculateBill(420);

Same strong typing. Same wire speed.60% less code for you - and for your AI - to read, write and review.

/FEATURE MATRIX

The honest, line-by-line comparison

CapabilityGRPC

PROGRAMMING MODEL

Call with Strongly Typed Methods without IDL

[×] NO

Regular Exception support

[×] NO

Complex DTOs & arrays passed by value in one call

[✓] YES

PROGRAMMING DEPENDENCIES & CONTRACTS

No additional SDK

[×] NO

No contract files

[×] NO

Use remote modules as dependencies

[-] PARTIAL

TOPOLOGY & TRANSPORT

Monolith <-> Microservices switch by configuration

[×] NO

Switch remote <-> in-memory with config only

[×] NO

TOPOLOGY & TRANSPORT

Same programming model for queues / event buses

[×] NO

Full streaming

[✓] YES

Automatic Native MCP

[×] NO

GRPC compared with Graftcode
Capability	GRPC	Graftcode
PROGRAMMING MODEL
Call with Strongly Typed Methods without IDL	[×] NO	[✓] YES
Regular Exception support	[×] NO	[✓] YES
Complex DTOs & arrays passed by value in one call	[✓] YES	[✓] YES
PROGRAMMING DEPENDENCIES & CONTRACTS
No additional SDK	[×] NO	[✓] YES
No contract files	[×] NO	[✓] YES
Use remote modules as dependencies	[-] PARTIAL	[✓] YES
TOPOLOGY & TRANSPORT
Monolith <-> Microservices switch by configuration	[×] NO	[✓] YES
Switch remote <-> in-memory with config only	[×] NO	[✓] YES
TOPOLOGY & TRANSPORT
Same programming model for queues / event buses	[×] NO	[✓] Via plugins
Full streaming	[✓] YES	[✓] YES
Automatic Native MCP	[×] NO	[✓] YES

/BY THE NUMBERS

The payoff, in numbers

60%

less code for AI to touch

1/8

of REST/RPC overhead via Hypertube™

coding languages supported

package managers supported

/FAQS

Before you ask

No. Hypertube™ connects language runtimes directly and skips the serialization overhead of HTTP-based transports — roughly 1/8 of REST/RPC overhead. In-process calls run at near-native speed. You keep gRPC-class performance without the gRPC-class boilerplate.

/COMMUNITY

Join grafters community

Many developers are loving Graftcode and what it brings to them.

“Graftcode appears to be an exceptionally useful platform. Its key value proposition is allowing developers to concentrate on core business requirements instead of tedious service integration tasks. I believe the concept of beginning with a monolithic structure and then having the option to dynamically transition to a microservice architecture will prove to be extremely valuable.”