What Is Idempotent in REST API? Definition and Examples

Idempotency is one of those API design principles that seems simple until you're debugging why customers got charged twice for the same transaction. At its core, an idempotent operation produces the same result whether you call it once or a hundred times, but implementing this correctly across different HTTP methods and real-world scenarios requires understanding the nuances of state management, client behavior, and system reliability.

This guide covers how to implement idempotency patterns in REST APIs, from the basic HTTP method behaviors to advanced techniques like idempotency keys and state validation. You'll learn which operations need idempotency protection, how to test your implementation, and why this becomes even more critical as AI agents start interacting with your APIs through tools and SDKs.

What is idempotency in REST APIs?

In a REST API, an operation is idempotent if making the same request multiple times has the exact same effect on the server's state as making it just once. This doesn't mean you get the same response every time, but it guarantees that repeating the request won't cause duplicate actions, like charging a credit card twice. Think of it like adding zero to a number; you can do it repeatedly, but the number doesn't change after the first time.

For example, if a client sends a POST /payments request and the network connection drops before a response is received, the client doesn't know if the payment was processed. Without idempotency, retrying the request could result in a double charge. An idempotent design prevents this. This concept is a core principle of HTTP, defined in RFC 9110, and it's the server's responsibility to enforce it.

Why idempotency matters for API reliability

Your API will inevitably receive duplicate requests. It's a fact of life in distributed systems, where clients operate on unreliable networks like mobile or Wi-Fi. A user's app might automatically retry a failed request, a backend process might crash and restart, or a simple network hiccup could cause a timeout.

Without idempotency, these retries can be dangerous.

• Business Risks: Duplicate requests can lead to double-charging customers, creating duplicate records, or sending multiple notifications for a single event.

• Data Corruption: Repeated updates can lead to inconsistent or incorrect data states, which are difficult to debug and fix.

• Poor Developer Experience: Users of your API are forced to build complex, fragile retry and de-duplication logic on their end, increasing their integration time and support burden.

A well-designed API handles this gracefully, which is why building a comprehensive API platform with proper tooling support has become so important. Modern client SDKs, for instance, often come with automatic retries for transient network errors, and the SDK generator can build these capabilities directly into your client libraries. To make this safe, they can be configured to send a unique Idempotency-Key header with each request. This allows your API to recognize retries and safely discard duplicates, simplifying client logic and making the entire system more robust.

Which HTTP methods are naturally idempotent?

The HTTP specification defines certain methods as idempotent by nature, while others are not. It's crucial to understand the difference between idempotent and safe methods. Safe methods, like GET, do not change the state of the server. All safe methods are idempotent, but not all idempotent methods are safe.

Safe methods

These methods are intended only for information retrieval and should never alter the server's state. Because they don't cause side effects, they are inherently idempotent.

• GET: Retrieves a resource. Calling it multiple times returns the same data without changing it.

• HEAD: Retrieves the headers for a resource, without the body. It's identical to GET but without the response body.

• OPTIONS: Describes the communication options for the target resource.

• TRACE: Performs a message loop-back test along the path to the target resource.

Idempotent write methods

These methods may change the server's state, but repeated identical requests will not change it further after the initial request.

• PUT: Replaces a target resource with the request payload. If you send the same PUT request to /users/123 ten times, the user's resource will be in the exact same state as it was after the first request.

• DELETE: Deletes a specified resource. The first DELETE /users/123 request deletes the user and likely returns a 200 OK or 204 No Content. Subsequent identical requests will find the user is already gone and return a 404 Not Found, but the server state (the user being deleted) remains unchanged.

Non-idempotent methods

These methods are expected to have different effects on the server each time they are called.

• POST: Typically used to create a new subordinate resource. Sending POST /users twice will create two distinct users.

• PATCH: Applies a partial modification to a resource. A request like PATCH /items/1 with instructions to {"increment": "quantity"} would increase the quantity with every call.

How to implement idempotency in your API

You don't need to make every endpoint idempotent overnight. Start with the most critical operations, especially POST requests that trigger payments, create important records, or have other significant side effects. The most common and robust way to achieve this is with an idempotency key.

Idempotency key pattern

This pattern involves the client generating a unique key for each operation it wants to make idempotent.

1. The client creates a unique identifier, typically a UUID, for a request.

2. It sends this key in a request header, such as Idempotency-Key: a1b2c3d4-e5f6-7890-g1h2-i3j4k5l6m7n8.

3. Your server sees this key for the first time, processes the request, and stores the result (the status code and body) mapped to that key before sending the response.

4. If a retry request arrives with the same key, the server skips the processing logic and immediately returns the stored response.

You should set a Time-to-Live (TTL) for these stored keys, typically 24 hours, to prevent them from accumulating indefinitely. For developers using SDKs generated from an OpenAPI spec, this entire flow can be automated, especially when creating OpenAPI specs with proper idempotency configurations in mind.

State validation pattern

For PUT or PATCH requests, you can use conditional headers like If-Match with an ETag value. This ensures that the client is updating the version of the resource they think they are, preventing lost updates and providing a form of idempotency based on resource state.

Request fingerprint pattern

An alternative to a client-sent key is to generate a "fingerprint" on the server by hashing the request's payload and other key properties. This can work but is more brittle; small, meaningless changes in the request (like whitespace) can result in a different hash, defeating the purpose. An explicit key sent by the client is almost always a better approach.

How idempotency supports AI and MCP integrations

As AI agents begin to interact with APIs, idempotency becomes even more critical. LLMs can be unpredictable; they might decide to retry an operation if they are uncertain about the outcome or if their internal logic dictates it. If an AI agent calls a non-idempotent create_invoice tool twice, you've just double-billed a customer without any human intervention.

This is where the Model Context Protocol (MCP) and robust SDKs become essential, and following a practical guide for MCP development can help structure your tools and workflows effectively. When an LLM interacts with your API through an MCP server, the flow looks like this:

LLM -> MCP Tool -> SDK Method -> API Call

If the SDK layer is built with idempotency, the entire stack becomes more reliable. For example, generating MCP servers from OpenAPI specs can expose your API endpoints as tools. When an LLM calls a tool that triggers a POST request, the underlying SDK can automatically attach an idempotency key, ensuring that even if the LLM retries the tool call, the action is only performed once. This makes your API safe for autonomous AI interaction.

Below is an example of a Stainless-generated MCP tool definition that leverages built-in idempotency support:

import { MyMcpClient, Endpoint } from 'my-org-name-mcp';

export const updateProductTool: Endpoint = {
  metadata: {
    resource: 'products',
    operation: 'update',
    // You can add tags or other metadata here if desired.
  },
  tool: {
    name: 'update_product_price',
    description: 'Updates a product price in an idempotent manner',
  },
  handler: async (client: MyMcpClient, args: { id: string; newPrice: number }) => {
    // The client automatically adds an Idempotency-Key on retries
    const updatedProduct = await client.products.update(args.id, {
      price: args.newPrice,
    });
    return { content: `Product ${updatedProduct.id} price updated.` };
  },
};

Test and validate idempotent behaviour

Implementing idempotency is only half the battle; you need to test it to ensure it works as expected. Your testing strategy should cover various scenarios to build confidence in your implementation. Some client libraries even include headers like X-Stainless-Retry-Count that can help you trace how many times a request was retried during a test.

Duplicate-request test cases

Write automated tests that send the same request twice in a row. Assert that the system state changed only once. For example, call POST /widgets with the same idempotency key twice and verify that only one widget was created in the database.

Concurrency test cases

Test what happens when two identical requests arrive at the exact same time. This helps validate your database locking or unique constraint strategy to ensure you don't have race conditions that bypass your idempotency check.

Monitoring indicators

In production, monitor key metrics related to your idempotency system. Track the number of idempotency key rejections (successful de-duplications), the latency of your idempotency key lookup, and the cache hit rate, while integrating SDK snippets with API documentation to help developers understand these patterns.

Frequently asked questions about idempotency in REST APIs

What is an example of an idempotent operation?

A classic example is using PUT /users/123 to update a user's email address. No matter how many times you send the exact same request, the user's email will be set to the new value and remain that way.

Is POST ever idempotent?

By default, POST is not idempotent, but you can make it behave idempotently by requiring an Idempotency-Key in the request header. This allows your server to recognize and de-duplicate repeated POST requests.

Why is PUT considered idempotent?

PUT is idempotent because its definition requires it to completely replace the target resource with the provided payload. Sending the same replacement payload multiple times results in the same final state for the resource.

Should every endpoint be idempotent?

Not necessarily. While critical, state-changing operations benefit greatly from idempotency, some endpoints might be intentionally non-idempotent. For example, an endpoint that logs an event, like /analytics/events, is designed to record every single call.

How do idempotency keys prevent duplicate payments?

When a payment request includes a unique idempotency key, the payment processor's server stores that key after successfully processing the payment. If a network error causes a retry with the same key, the server sees the key, recognizes the duplicate, and returns the original success response without processing the payment again.

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