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Mock Llm

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MCP server to mock OpenAI, Anthropic, and Google Gemini responses for testing AI integrations without real API keys or token spend.

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About

MCP server to mock OpenAI, Anthropic, and Google Gemini responses for testing AI integrations without real API keys or token spend.

README

MCP server for Mock LLM API — mock OpenAI, Anthropic, and Google Gemini responses for testing AI integrations. No real API keys or token spend required.

Installation

pip install mock-llm-mcp
# or
uvx mock-llm-mcp

Claude Desktop Configuration

{
  "mcpServers": {
    "mock-llm": {
      "command": "uvx",
      "args": ["mock-llm-mcp"],
      "env": {
        "MOCK_LLM_API_KEY": "your-key-here"
      }
    }
  }
}

No API key required for the free tier (500 calls/day). Get a key at rebaselabs.online for higher limits.

Tools

Tool Description
mock_quick Quickest mock response — provider-agnostic, auto-detects response type
mock_openai_chat Drop-in mock for POST /v1/chat/completions (OpenAI format)
mock_anthropic_message Drop-in mock for POST /v1/messages (Anthropic format)
mock_google_generate Drop-in mock for Google Gemini generateContent
mock_simulate_error Simulate specific LLM errors (rate limit, timeout, invalid key, etc.)
list_mock_models List available mock models for a provider

Use Cases

  • Test without token spend — verify your LLM integration code works without calling real APIs
  • CI/CD pipelines — deterministic, offline-safe tests using seed-based responses
  • Error handling — simulate rate limits, 500 errors, auth failures, context length exceeded
  • Frontend dev — build chat UIs without a real API key
  • Multi-provider testing — test your abstraction layer against OpenAI, Anthropic, and Google formats

Examples

Quick mock (no format needed)

mock_quick(prompt="Explain quantum computing", length="short")

Test OpenAI integration

mock_openai_chat(
    messages=[{"role": "user", "content": "Hello!"}],
    model="gpt-4o",
    response_type="text"
)

Simulate a rate limit error

mock_simulate_error(provider="anthropic", error_type="rate_limit")

Deterministic response with seed

mock_quick(prompt="Write a haiku", seed=42)

Response Control Headers

All mock tools support:

  • length: "short", "medium", "long", "xl", "random"
  • response_type: "auto", "text", "code", "json", "markdown", "list"
  • error: "none", "rate_limit", "server_error", "timeout", "invalid_key", "context_length", "content_filter"
  • delay_ms: 05000 — artificial latency
  • seed: integer — reproducible responses

Environment Variables

Variable Description Default
MOCK_LLM_API_KEY API key for authenticated access `` (free tier)
MOCK_LLM_API_URL Override API base URL https://mock-llm-api.rebaselabs.online

Part of the RebaseKit Agent Infrastructure Stack

Mock LLM MCP is part of the RebaseKit suite of agent-native APIs:

  • WeTask — web extraction & browser automation
  • CodeExec — sandboxed code execution
  • PII API — detect & mask sensitive data
  • DocParse — document parsing & OCR
  • DataTransform — data format conversion & querying
  • Mock LLM — mock any LLM provider for testing

"The internet was built for humans. RebaseKit makes it work for agents."

from github.com/rebaselabs-framework/mock-llm-mcp

Install Mock Llm in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install mock-llm-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add mock-llm-mcp -- uvx --from git+https://github.com/rebaselabs-framework/mock-llm-mcp mock-llm-mcp

FAQ

Is Mock Llm MCP free?

Yes, Mock Llm MCP is free — one-click install via Unyly at no cost.

Does Mock Llm need an API key?

No, Mock Llm runs without API keys or environment variables.

Is Mock Llm hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Mock Llm in Claude Desktop, Claude Code or Cursor?

Open Mock Llm on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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