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@copilotkit/aimock

Mock infrastructure for AI application testing — LLM APIs, image generation, image editing, text-to-speech, transcription, audio translation, audio generation, video generation, embeddings, MCP tools,

615 stars575k/wkupdated 0d agogithub ↗
86good
▣ Overview
Unit TestsDrift Testsnpm version

What it does

aimock is a local mock server for testing AI applications. It simulates 14 LLM providers (OpenAI, Anthropic Claude, Gemini, Bedrock, Ollama, and others), multimedia services (image generation, text-to-speech, transcription, video), MCP tool execution, vector databases (Pinecone, Qdrant, ChromaDB), and supporting APIs (search, reranking, moderation). It runs on a single port with zero production dependencies and supports recording real API calls as fixtures for deterministic replay in tests, including timing-aware reproduction of streaming behavior.

Who it's for

Backend developers and QA engineers testing AI-powered applications, particularly those with multiple LLM provider integrations, tool execution, vector retrieval, or multimedia processing. Common in CI/CD environments where isolating external API dependencies reduces costs and iteration time.

Common use cases

  • Unit test LLM-dependent code paths without incurring OpenAI, Anthropic, or other provider costs
  • Record multi-turn production conversations and tool-calling traces, replay them deterministically in CI
  • Validate MCP tool execution, A2A (agent-to-agent), and AG-UI (agent-to-UI) event streams
  • Test RAG flows by mocking Pinecone, Qdrant, or ChromaDB endpoints
  • Test image generation, audio transcription, or video processing workflows in isolation

Setup pitfalls

  • Environment variables (like OPENAI_BASE_URL) must be set before importing the provider SDK—many SDKs cache the base URL at construction time, risking real API calls if set after import
  • One secret was detected in the repository—review credential handling and .gitignore
  • Reads and writes filesystem for record/replay fixtures—verify directory permissions in restricted CI environments
  • High risk classification—ensure proper network isolation when running in multi-tenant or shared CI systems
1 credential detected in repository history via Gitleaks
▣ Score BreakdownMCPScore = Σ(raw × weight)
DimensionRawWeighted
Security
35%
80
28.0
Freshness
25%
100
25.0
Adoption
20%
88
17.6
Quality
10%
100
10.0
Trust
10%
50
5.0
Total
85.6
⚿ Capabilities & Risk Explainer
fs readfs writenetworkexecsecrets
◆ Risk level: high
fs read + fs write + network + exec + secrets active — can execute code, access credentials, and make external network calls.
⚙ Install config
Claude Desktop · Cursor · Windsurf · VS Code (Copilot) · Claude Code
add to your MCP client config:
{
  "mcpServers": {
    "copilotkitaimock": {
      "command": "npx",
      "args": [
        "-y",
        "@copilotkit/aimock"
      ]
    }
  }
}
📈 Score historylast 18 snapshots
5/25/20266/11/2026 · 18 snapshots
⚙ Maintenance health
maintenance data not yet available — check back later.
⛁ Raw data
weekly downloads575k
github stars615
forks40
open issues3
license✓ present
readme length12090 chars
last publish0d ago
last commit0d ago
last updated7d ago
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