Configuration

MCP Stress Test can be configured through three methods, listed in order of precedence (highest first):

1. CLI flags — Override any setting for a single command.
2. Config file — A JSON file loaded via --config / -c flag.
3. Environment variables — Prefixed with MCP_STRESS_.

If no configuration is provided, sensible defaults are used.

Config file

Create a stress-config.json file:

{
  "llm": {
    "provider": "ollama",
    "model": "llama3.2",
    "base_url": "http://localhost:11434",
    "temperature": 0.7,
    "max_tokens": 500,
    "timeout_seconds": 30
  },
  "scanner": {
    "default_scanner": "mock",
    "tool_scan_path": null,
    "timeout_ms": 5000,
    "retry_count": 3
  },
  "report": {
    "default_format": "markdown",
    "output_dir": "./reports",
    "include_raw_results": false,
    "html_template": null
  },
  "fuzz": {
    "max_generations": 10,
    "mutation_rate": 0.3,
    "evasion_threshold": 0.5,
    "save_evasions": true,
    "evasion_output_dir": "./evasions"
  },
  "chain": {
    "max_chain_length": 5,
    "step_delay_ms": 100,
    "fail_fast": false
  },
  "verbose": false,
  "parallel_workers": 1,
  "cache_results": true,
  "cache_dir": "./.stress-cache"
}

Pass it to any command:

mcp-stress -c stress-config.json scan compare -t read_file -s obfuscation

Configuration sections

LLM (llm)

Controls the Ollama connection used for LLM-guided fuzzing.

Field	Type	Default	Description
provider	string	"ollama"	LLM provider (currently only ollama)
model	string	"llama3.2"	Ollama model name
base_url	string	"http://localhost:11434"	Ollama API base URL
temperature	float	0.7	Sampling temperature for mutations
max_tokens	int	500	Max tokens per LLM response
timeout_seconds	int	30	Request timeout

Scanner (scanner)

Controls which scanner is used and how it behaves.

Field	Type	Default	Description
default_scanner	string	"mock"	Scanner to use: mock, tool-scan, or cli
tool_scan_path	string	null	Path to tool-scan binary (auto-detected if on PATH)
timeout_ms	int	5000	Scan timeout per tool
retry_count	int	3	Retries on scanner failure

Report (report)

Controls report generation defaults.

Field	Type	Default	Description
default_format	string	"markdown"	Default output format
output_dir	string	"./reports"	Directory for report output
include_raw_results	bool	false	Include raw scan data in reports
html_template	string	null	Custom Jinja2 template for HTML reports

Fuzz (fuzz)

Controls fuzzing behavior and evasion testing.

Field	Type	Default	Description
max_generations	int	10	Maximum mutation generations per run
mutation_rate	float	0.3	Probability of mutating each token
evasion_threshold	float	0.5	Scanner score below which evasion is declared
save_evasions	bool	true	Automatically save discovered evasions
evasion_output_dir	string	"./evasions"	Directory for saved evasions

Chain (chain)

Controls attack chain execution.

Field	Type	Default	Description
max_chain_length	int	5	Maximum steps in a chain
step_delay_ms	int	100	Delay between chain steps
fail_fast	bool	false	Stop chain on first detection

Global settings

Field	Type	Default	Description
verbose	bool	false	Enable verbose output
parallel_workers	int	1	Number of parallel workers
cache_results	bool	true	Cache scan results
cache_dir	string	"./.stress-cache"	Cache directory

Environment variables

Every config field has a corresponding environment variable prefixed with MCP_STRESS_:

Variable	Maps to
MCP_STRESS_LLM_MODEL	llm.model
MCP_STRESS_LLM_URL	llm.base_url
MCP_STRESS_LLM_PROVIDER	llm.provider
MCP_STRESS_SCANNER_DEFAULT	scanner.default_scanner
MCP_STRESS_TOOL_SCAN_PATH	scanner.tool_scan_path
MCP_STRESS_REPORT_FORMAT	report.default_format
MCP_STRESS_REPORT_DIR	report.output_dir
MCP_STRESS_VERBOSE	verbose (accepts true, 1, yes)
MCP_STRESS_WORKERS	parallel_workers

Example:

export MCP_STRESS_LLM_MODEL=codellama
export MCP_STRESS_SCANNER_DEFAULT=tool-scan
mcp-stress scan compare -t read_file -s obfuscation

Python programmatic config

When using the Python API, create a StressConfig directly:

from mcp_stress_test.core.config import StressConfig, LLMConfig, ScannerConfig

config = StressConfig(
    llm=LLMConfig(model="codellama", temperature=0.9),
    scanner=ScannerConfig(default_scanner="tool-scan"),
    verbose=True,
)

# Or load from file
config = StressConfig.from_file("stress-config.json")

# Or load from environment
config = StressConfig.from_env()

# Save current config
config.save("my-config.json")