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AgentBreak

Chaos proxy for testing how your agents handle failures. Sits between your agent and the LLM/MCP server, injects faults.

Agent  -->  AgentBreak (localhost:5005)  -->  Real LLM / MCP server
                     ^
          .agentbreak/scenarios.yaml defines faults

Quick start

pip install agentbreak
agentbreak init       # creates .agentbreak/ with default configs
agentbreak serve      # start the chaos proxy

Point your agent at http://localhost:5005 instead of the real API:

  • OpenAI SDK: set OPENAI_BASE_URL=http://localhost:5005/v1
  • Anthropic SDK: set ANTHROPIC_BASE_URL=http://localhost:5005

Check results:

curl localhost:5005/_agentbreak/scorecard

Config

.agentbreak/application.yaml -- what to proxy:

llm:
  enabled: true
  mode: mock           # mock (no API key needed) or proxy (forwards to upstream)
mcp:
  enabled: false       # set true + upstream_url for MCP testing
serve:
  port: 5005

.agentbreak/scenarios.yaml -- what faults to inject:

version: 1
scenarios:
  - name: slow-llm
    summary: Latency spike on completions
    target: llm_chat
    fault:
      kind: latency
      min_ms: 2000
      max_ms: 5000
    schedule:
      mode: random
      probability: 0.3

Or use a preset: brownout, mcp-slow-tools, mcp-tool-failures, mcp-mixed-transient.

Fault kinds

http_error, latency, timeout (MCP only), empty_response, invalid_json, schema_violation, wrong_content, large_response

MCP testing

agentbreak inspect    # discover tools from upstream MCP server
agentbreak serve      # proxy both LLM and MCP traffic

CLI

agentbreak init       # create .agentbreak/ config
agentbreak serve      # start proxy
agentbreak validate   # check config
agentbreak inspect    # discover MCP tools
agentbreak verify     # run tests

Claude Code skill

npx skills add mnvsk97/agentbreak

Then use /agentbreak to chaos-test your agent with a guided workflow.

Examples

See examples/ for sample agents and MCP servers with various auth configs.