Mimicly
OpenAI-compatible endpoint · Drop-in mocking & testing

Test AI applications without calling real AI APIs every time.

Record real AI interactions, turn them into deterministic mocks, simulate failures, and run reliable tests in development, staging and CI.

Explore the Concept
No credit card required
Zero production changes
Built for solo developers & small AI teams
Any OpenAI SDK · TypeScript · Python · Go · Node.js
100% Flake-free
Deterministic
4ms Latency
Zero lag
OpenAI Compatible
More on the way
Record & Replay
1-click fixtures
Development & CI
Mock Active
Your AI App
localhost:3000
POST /chat/completions

Mimicly Mock Engine

Exact payload match found

4ms
Deterministic Mock Output
200 OK · 0 tokens billed
$0.00
Production
Live Provider
Your AI App
api.app.com
Direct HTTPS
Live AI Providersapi.openai.com
OpenAI
A\Claude
Gemini
Full Generation
3,420ms · 1,420 tokens
$0.04

1. Record

2. Mock

3. Test

Record → Replay

Record once, replay the same mock in dev, staging and CI.

429 · 500 · timeout

Simulate provider rate limits and server crashes on demand.

One env var

Swap the base URL, ship the exact same code to production.

Zero token spend

Eliminate API billing and rate limit flakiness in CI pipelines.

Built for the providers AI teams already use

An OpenAI-compatible mock endpoint today, with the other major providers on the roadmap.

OpenAIMVP target
AnthropicComing soon
Google GeminiComing soon
Azure OpenAIComing soon
The Operational Bottleneck

Real AI APIs are great for production. They break your CI and developer flow.

Calling live LLMs on every automated test run introduces flakiness, unexpected monthly token bills, and slow 45-second CI pipelines.

Non-deterministic responses

LLMs can return different output for similar input. A test that passes today can behave differently tomorrow, for no reason your test suite can explain.

Repeated API costs

Hundreds of automated test runs against a real LLM API add up in token spend, especially in CI where the same tests run on every commit.

Rate limits

Parallel test runs and CI pipelines can trigger 429s and provider throttling, turning a flaky provider limit into a flaky test suite.

Slow test suites

Real network latency and model processing time add seconds to every call. Multiply that by hundreds of tests and CI gets slow.

Hard-to-reproduce failures

429s, timeouts, malformed responses, invalid keys and streaming failures are difficult and expensive to trigger reliably against a real provider.

CI/CD provider dependency

Tests that depend on an external provider's availability aren't fully predictable, repeatable, or independent of that provider's uptime.

See it in action

From real traffic to reliable mocks in minutes

No new SDK to learn. Point your existing OpenAI client at Mimicly's base URL and record, mock and test from there.

1import OpenAI from "openai";
2
3const client = new OpenAI({
4 apiKey: process.env.OPENAI_API_KEY,
5 baseURL: process.env.AI_BASE_URL,
6});
1

Record real request

Capture actual API interactions from your application.

2

Create mock

Edit or generate deterministic responses with ease.

3

Run tests

Validate your application in dev, staging or CI.

Test resultsPassed
Mock response returned
Response time 4ms
Schema validation 100%
No live API token spent
Deterministic run:0 flakiness
Why Choose Mimicly

Built specifically for testing AI applications

Generic HTTP mocking tools don't understand LLM schemas, streaming tokens, or provider rate limits the way a purpose-built AI mock does.

Testing Against Live AI APIs

  • Token costs that multiply with every pull request & commit
  • Flaky CI builds triggered by external LLM provider outages
  • Real network + model generation latency on every call

The Mimicly Mock Engine

Built for AI
  • $0 token cost in development, staging & CI
  • Deterministic — identical tests produce reproducible results
  • Instant 4ms responses with zero network round trips
Feature / CapabilityMimiclyLive AI APIsGeneric HTTP MocksStatic JSON Fixtures
Zero token billing during tests
Deterministic, flake-free CI runs
One-step recording from real traffic
Provider error simulation (429 / 500 / timeout)partial
Zero production changes (1 env var)complexcomplex
Target Use Cases

Engineered for high-velocity AI engineering teams

From conversational agents to complex RAG pipelines, test every AI branch without breaking production or budget.

AI chatbots

Test predictable conversation flows without depending on live model output.

RAG applications

Test retrieval plus generation as one workflow, with a fixed generation step.

AI agents

Test multi-step tool calls and agent decisions against known, repeatable responses.

AI customer support

Reproduce edge cases and failure states that are hard to trigger from a real provider.

AI document processing

Test extraction and structured-output handling against fixed model output.

AI automation

Run repeatable integration tests for pipelines that call an LLM as one step.

Matching Strategies

Flexible matching for real-world scenarios

A mock doesn't require an identical request every time. Choose the matching strategy that fits each test case.

Exact match

The same request returns the same recorded response.

request === recorded request → recorded response

Endpoint match

Match on HTTP method and endpoint, regardless of payload.

POST /v1/chat/completions → mocked response

Pattern match

Match when the request content contains a pattern you define.

"cancel my order" → cancellation mock

Scenario match

Trigger a named scenario explicitly from your test.

scenario: "order-cancellation" → predefined response
Free during beta

Start testing free. Pricing is still being validated.

Every plan is free while we're in private beta — no card required. The numbers below are what we're planning to charge afterward, not a bill you'll see today.

Currency

Mimicly isn't available yet — these plans show how we'd expect to offer it. Explore the concept.

Starter

For individual developers & side projects
Freeduring beta
Stays free / month after beta

Essential deterministic mocking and record-replay for solo AI developers.

What is included:

  • 1,000 mock requests / month
  • Record & replay engine
  • Exact & pattern matching
  • Request logs inspection
  • Community GitHub support
Explore the Concept
Most Popular

Developer

For active developers & fast releases
Freeduring beta
Planned at $9 / month after beta

Full failure simulation and unlimited projects for engineering workflows.

What is included:

  • 10,000 mock requests / month
  • Unlimited projects & test suites
  • 429 rate limit & timeout simulation
  • GitHub Actions & GitLab CI integration
  • Detailed request diffs & schema validation
  • Priority email support
Explore the Concept

Team

For growing AI engineering teams
Freeduring beta
Planned at $29 / month after beta

Shared workspaces, multi-provider mocking, and advanced scenario branching.

What is included:

  • 100,000 mock requests / month
  • Unlimited team seats & workspaces
  • OpenAI, Claude, Gemini & Azure mocks
  • Scenario branching & versioning
  • Custom latency injection profiles
  • Shared Slack & priority support
Explore the Concept
Free during beta testing•Instant 1-env-var drop-in•Zero Production Changes•Cancel Anytime
Security & Privacy

AI prompts and responses can be sensitive. We treat them that way.

We don't claim certifications we don't have. Here's what's actually true today.

Provider keys stay encrypted

API keys used for recording are encrypted and never logged in plain text.

Zero training on your data

Your recorded prompts, schemas, and payload responses are never used to train any model.

You control your data

Delete a recording, a mock, or your entire project at any time. Automated retention rules are on the roadmap.

Encrypted at rest and in transit

Recordings and mocks are encrypted at rest and transferred over HTTPS.

Questions & Answers

Frequently asked questions

Everything you need to know about integrating Mimicly into your development workflow.

You can, and plenty of teams start there. That works until you need real recorded traffic instead of hand-written payloads, provider-specific failure shapes (429s, timeouts, malformed responses), and a matching layer that doesn't need updating every time a schema changes. Mimicly exists for that point, not to replace a five-line stub.
No. Mimicly is for development, staging and testing. Production continues to call OpenAI, Anthropic, Gemini or whichever provider you already use.
Ideally, only the base URL or API configuration used in your test environment. Your production configuration stays as it is.
The MVP primarily replays recorded or manually configured responses. It does not require, and is not, its own LLM.
Yes. You can configure controlled scenarios such as 429 rate limits, 500 errors and timeouts, and trigger them on demand from your tests.
Yes, the architecture is designed for automated test environments. Point your CI configuration at the mock endpoint the same way you would in staging.
No. Production keeps using your existing provider configuration. Mimicly only sits in your development, staging and CI paths.
Recordings are stored so they can be replayed as mocks. You can delete recordings you no longer need. We do not use your prompts or responses to train any model.
Ready to Streamline Your AI Testing?

Record one real interaction. Replay it as many times as your test suite needs.

Zero token cost in CI. Zero flakiness. Instant 4ms response times.

Explore the ConceptView Pricing Plans
No credit card required • Free plan available • 1 env var setup