Skip to main content
Glama

mock-llm-mcp

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

Related MCP server: mcp-consultant

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."

Related MCP Connectors

Related MCP Servers

  • A
    license
    B
    quality
    D
    maintenance
    A mock MCP server for testing MCP client implementations and development workflows. Supports tools, prompts, and resources across multiple transport protocols (stdio, HTTP, SSE).
    1
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    MCP server that interfaces with Gemini and OpenAI CLI tools to enable AI model interactions. It provides a bridge to external AI CLIs with predefined model configurations.
    -
  • A
    license
    A
    quality
    C
    maintenance
    An MCP server for interacting with MockServer, enabling AI assistants to create mock HTTP expectations, verify requests, clear state, and manage MockServer instances programmatically.
    6
    37 npm
    1
    MIT