High Risk →

ab_experiments_start

Start a draft A/B testing experiment so variants begin serving to targeted users and data collection begins. Requires the ab-testing plugin. To halt a running experiment use ab_experiments_stop.

Part of the Countly MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

AI agents invoke ab_experiments_start to trigger processes or run actions in Countly. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

ab_experiments_start can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

countly.yaml
tools:
  ab_experiments_start:
    rules:
      - action: allow
        rate_limit:
          max: 10
          window: 60
        validate:
          required_args: true

See the full Countly policy for all 127 tools.

Tool Name ab_experiments_start
Category Execute
MCP Server Countly MCP Server
Risk Level High

View all 127 tools →

Agents calling execute-class tools like ab_experiments_start have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

ab_experiments_start is one of the high-risk operations in Countly. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.

What does the ab_experiments_start tool do? +

Start a draft A/B testing experiment so variants begin serving to targeted users and data collection begins. Requires the ab-testing plugin. To halt a running experiment use ab_experiments_stop.. It is categorised as a Execute tool in the Countly MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on ab_experiments_start? +

Add a rule in your Intercept YAML policy under the tools section for ab_experiments_start. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Countly MCP server.

What risk level is ab_experiments_start? +

ab_experiments_start is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit ab_experiments_start? +

Yes. Add a rate_limit block to the ab_experiments_start rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block ab_experiments_start completely? +

Set action: deny in the Intercept policy for ab_experiments_start. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides ab_experiments_start? +

ab_experiments_start is provided by the Countly MCP server (countly-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Let agents act without letting them run wild.

Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.

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