Set or update an environment variable for your Rails application on Hatchbox. This tool uses the Hatchbox API to modify environment variables, which will be applied on the next deployment. Changes do not take effect immediately - you must trigger a deployment after setting variables. Example resp...
AI agents use setEnvVar to create or update resources in Langfuse Observability — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Langfuse Observability environment.
This tool modifies application configuration through environment variables, which is a reversible Write operation. However, the severity is high because environment variables control critical application behavior including feature flags, API endpoints, credentials, and external service URLs. Misuse could disable security features, redirect traffic, expose credentials, or degrade performance.
From the tool's definition Tool description states it 'Set or update an environment variable' and uses 'Hatchbox API to modify environment variables'. The example shows successful modification: 'Successfully set environment variable: FEATURE_FLAG_ENABLED=true'.
Attacks that exploit this kind of access
Set or update an environment variable for your Rails application on Hatchbox. This tool uses the Hatchbox API to modify environment variables, which will be applied on the next deployment. Changes do not take effect immediately - you must trigger a deployment after setting variables. Example response: Successfully set environment variable: FEATURE_FLAG_ENABLED=true Use cases: - Enabling or disabling feature flags - Updating API endpoints or external service URLs - Changing application configuration values - Setting new API keys or credentials - Adjusting performance tuning parameters - Configuring third-party service integrations Important notes: - Changes require a deployment to take effect - Use getEnvVars to verify current values before changes - Requires READONLY=false in configuration - Some variables like RAILS_ENV should be changed with caution. It is categorised as a Write tool in the Langfuse Observability MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Langfuse Observability MCP server in PolicyLayer and add a rule for setEnvVar: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Langfuse Observability. Nothing to install.
setEnvVar is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the setEnvVar rule in your PolicyLayer 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.
Set action: deny in the PolicyLayer policy for setEnvVar. 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.
setEnvVar is provided by the Langfuse Observability MCP server (langfuse-observability-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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