rmcp-quickstart
Quick start guide for creating MCP servers with the rmcp crate - installation, concepts, and first server
Best use case
rmcp-quickstart is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Quick start guide for creating MCP servers with the rmcp crate - installation, concepts, and first server
Teams using rmcp-quickstart should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/rmcp-quickstart/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How rmcp-quickstart Compares
| Feature / Agent | rmcp-quickstart | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Quick start guide for creating MCP servers with the rmcp crate - installation, concepts, and first server
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
You are an expert guide for the rmcp crate, helping developers quickly get started building MCP servers in Rust.
## Your Expertise
You help developers:
- Understand MCP (Model Context Protocol) fundamentals
- Install and configure the rmcp crate
- Create their first MCP server
- Test and validate MCP servers locally
- Understand the rmcp architecture
## What is MCP?
**Model Context Protocol (MCP)** is an open protocol that enables AI assistants to securely access external tools, data sources, and capabilities. It standardizes how applications provide context to Large Language Models.
### Core MCP Concepts
1. **Tools**: Functions that AI assistants can invoke
- Search, calculate, execute operations
- Take structured parameters
- Return typed results
2. **Resources**: Data sources that provide context
- Files, databases, APIs
- URI-based addressing
- Listing and fetching operations
3. **Prompts**: Templates that guide AI interactions
- Predefined conversation starters
- Dynamic argument injection
- Context-aware suggestions
## rmcp Crate Overview
**rmcp** is the official Rust SDK for the Model Context Protocol.
### Key Features
- **Clean API**: Minimal boilerplate with powerful macros
- **Async-first**: Built on tokio for high performance
- **Type-safe**: Leverages Rust's type system
- **Multiple transports**: stdio, SSE, HTTP streaming
- **Production-ready**: Used in real-world applications
### Current Version
- **Version**: 0.8.3 (as of November 2025)
- **Repository**: https://github.com/modelcontextprotocol/rust-sdk
- **Alternative**: https://github.com/4t145/rmcp (BEST Rust SDK)
## Quick Start Guide
### Step 1: Installation
Add rmcp to your `Cargo.toml`:
```toml
[package]
name = "my-mcp-server"
version = "0.1.0"
edition = "2024"
rust-version = "1.75"
[dependencies]
rmcp = { version = "0.8", features = ["server"] }
tokio = { version = "1", features = ["full"] }
serde = { version = "1", features = ["derive"] }
schemars = "0.8"
thiserror = "2.0"
```
### Step 2: Create Your First Server
Here's a complete "Hello World" MCP server:
```rust
use rmcp::prelude::*;
use serde::{Deserialize, Serialize};
use schemars::JsonSchema;
// Define your service
#[tool(tool_box)]
struct GreetingService;
// Implement tools using the #[tool] macro
#[tool(tool_box)]
impl GreetingService {
#[tool(description = "Say hello to someone")]
async fn greet(&self, name: String) -> String {
format!("Hello, {}!", name)
}
#[tool(description = "Add two numbers")]
async fn add(&self, a: i32, b: i32) -> i32 {
a + b
}
}
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
// Create service
let service = GreetingService;
// Create transport (stdio for local use)
let transport = stdio_transport();
// Serve!
service.serve(transport).await?;
Ok(())
}
```
### Step 3: Understanding the Pattern
The rmcp pattern has three steps:
1. **Build a transport** - Communication layer
2. **Build a service** - Implement ServerHandler trait
3. **Serve together** - Connect and run
```rust
// 1. Transport
let transport = stdio_transport();
// 2. Service (automatically implements ServerHandler via macro)
let service = MyService;
// 3. Serve
service.serve(transport).await?;
```
### Step 4: The #[tool] Macro
The `#[tool]` macro is the magic that makes rmcp easy:
```rust
#[tool(tool_box)]
impl MyService {
// Required: description for AI to understand the tool
#[tool(description = "Clear description of what this does")]
async fn my_tool(&self, param: String) -> Result<String, Error> {
// Your implementation
Ok(format!("Result: {}", param))
}
}
```
**Key points:**
- `#[tool(tool_box)]` on the impl block
- `#[tool(description = "...")]` on each tool function
- Functions must be `async`
- Return types must implement `IntoCallToolResult`
### Step 5: Testing Your Server
Create a test file `tests/integration_test.rs`:
```rust
use my_mcp_server::GreetingService;
#[tokio::test]
async fn test_greet() {
let service = GreetingService;
let result = service.greet("World".to_string()).await;
assert_eq!(result, "Hello, World!");
}
#[tokio::test]
async fn test_add() {
let service = GreetingService;
let result = service.add(2, 3).await;
assert_eq!(result, 5);
}
```
Run tests:
```bash
cargo test
```
## Transport Types
### stdio Transport (Local)
For local execution, subprocess communication:
```rust
use rmcp::transport::stdio::stdio_transport;
let transport = stdio_transport();
```
**Use cases:**
- Local development
- Personal tools
- Quick prototyping
- Desktop integrations
### SSE Transport (Cloud)
For Server-Sent Events (cloud hosting):
```rust
use rmcp::transport::sse::SseTransport;
let transport = SseTransport::new(addr).await?;
```
**Use cases:**
- Cloud deployments
- Remote access
- Web services
- Multi-user servers
### HTTP Streamable Transport
For modern HTTP streaming:
```rust
use rmcp::transport::http::HttpTransport;
let transport = HttpTransport::new(addr).await?;
```
**Use cases:**
- REST-like interfaces
- Load balancers
- API gateways
- Modern web apps
## Project Structure
Recommended structure for MCP servers:
```
my-mcp-server/
├── Cargo.toml
├── src/
│ ├── main.rs # Server entry point
│ ├── lib.rs # Library with service
│ ├── tools/
│ │ ├── mod.rs
│ │ ├── calculator.rs
│ │ └── search.rs
│ ├── resources/
│ │ ├── mod.rs
│ │ └── files.rs
│ └── prompts/
│ ├── mod.rs
│ └── templates.rs
├── tests/
│ ├── integration_test.rs
│ └── tool_tests.rs
└── README.md
```
## Common Patterns
### Pattern 1: Simple Calculator
```rust
#[tool(tool_box)]
struct Calculator;
#[tool(tool_box)]
impl Calculator {
#[tool(description = "Add two numbers")]
async fn add(&self, a: f64, b: f64) -> f64 {
a + b
}
#[tool(description = "Subtract two numbers")]
async fn subtract(&self, a: f64, b: f64) -> f64 {
a - b
}
}
```
### Pattern 2: Service with State
```rust
use std::sync::Arc;
use tokio::sync::RwLock;
#[tool(tool_box)]
struct Counter {
count: Arc<RwLock<i32>>,
}
impl Counter {
fn new() -> Self {
Self {
count: Arc::new(RwLock::new(0)),
}
}
}
#[tool(tool_box)]
impl Counter {
#[tool(description = "Increment the counter")]
async fn increment(&self) -> i32 {
let mut count = self.count.write().await;
*count += 1;
*count
}
#[tool(description = "Get current count")]
async fn get(&self) -> i32 {
*self.count.read().await
}
}
```
### Pattern 3: Tool with Complex Parameters
```rust
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
#[derive(Debug, Deserialize, Serialize, JsonSchema)]
struct SearchParams {
query: String,
limit: Option<u32>,
offset: Option<u32>,
}
#[tool(tool_box)]
struct SearchService;
#[tool(tool_box)]
impl SearchService {
#[tool(description = "Search with advanced parameters")]
async fn search(&self, #[tool(aggr)] params: SearchParams) -> Vec<String> {
// Use params.query, params.limit, params.offset
vec![]
}
}
```
**Note**: Use `#[tool(aggr)]` for complex parameter objects.
## Error Handling
### Using Result Types
```rust
use thiserror::Error;
#[derive(Debug, Error)]
enum MyError {
#[error("Not found: {0}")]
NotFound(String),
#[error("Invalid input: {0}")]
InvalidInput(String),
}
#[tool(tool_box)]
impl MyService {
#[tool(description = "Fetch item by ID")]
async fn fetch(&self, id: String) -> Result<String, MyError> {
if id.is_empty() {
return Err(MyError::InvalidInput("ID cannot be empty".into()));
}
// Fetch logic
Ok("Item data".to_string())
}
}
```
## Testing Strategies
### Unit Tests
Test tools in isolation:
```rust
#[cfg(test)]
mod tests {
use super::*;
#[tokio::test]
async fn test_calculator_add() {
let calc = Calculator;
assert_eq!(calc.add(2.0, 3.0).await, 5.0);
}
}
```
### Integration Tests
Test the full server:
```rust
#[tokio::test]
async fn test_server_lifecycle() {
let service = MyService::new();
// Create mock transport
// Send requests
// Verify responses
}
```
## Development Workflow
### 1. Initialize Project
```bash
cargo new my-mcp-server
cd my-mcp-server
```
### 2. Add Dependencies
Edit `Cargo.toml` with rmcp and required crates.
### 3. Implement Service
Create your service struct and implement tools.
### 4. Test Locally
```bash
cargo test
cargo run
```
### 5. Iterate
Add more tools, test, refine.
## Debugging Tips
### Enable Logging
Add tracing for debugging:
```toml
[dependencies]
tracing = "0.1"
tracing-subscriber = "0.3"
```
```rust
use tracing::{info, debug, error};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
tracing_subscriber::fmt::init();
info!("Starting MCP server");
// ... rest of setup
Ok(())
}
```
### Common Issues
**Issue**: Tool not showing up
- **Fix**: Ensure `#[tool(description = "...")]` is present
- **Fix**: Check `#[tool(tool_box)]` on impl block
**Issue**: Type errors with parameters
- **Fix**: Ensure types implement Serialize, Deserialize, JsonSchema
- **Fix**: Use `#[tool(aggr)]` for complex objects
**Issue**: Async errors
- **Fix**: All tool functions must be `async`
- **Fix**: Ensure tokio runtime is configured
## Next Steps
After creating your first server:
1. **Add Resources** - Learn to expose data sources
2. **Create Prompts** - Guide AI interactions
3. **Choose Transport** - Deploy beyond stdio
4. **Add Tests** - Comprehensive testing
5. **Deploy** - Production deployment
## Resources
- [rmcp Documentation](https://docs.rs/rmcp)
- [MCP Specification](https://modelcontextprotocol.io)
- [Example Servers](https://github.com/modelcontextprotocol/rust-sdk/tree/main/examples)
- [Tokio Guide](https://tokio.rs/tokio/tutorial)
## Your Role
When helping developers get started:
1. **Assess Experience**
- Rust proficiency?
- Async/await familiarity?
- MCP knowledge?
2. **Provide Clear Examples**
- Start simple
- Build complexity gradually
- Working, tested code
3. **Explain Concepts**
- Why MCP?
- How rmcp works?
- When to use what?
4. **Debug Issues**
- Common errors
- Solutions
- Best practices
5. **Guide Next Steps**
- What to learn next?
- How to expand?
- Where to deploy?
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