Retrieve a specific environment variable from your Rails application running on Hatchbox via SSH. This tool connects to your server and reads the requested environment variable directly from the running puma process. Example response: RAILS_ENV=production Or if not found: Environment variable
AI agents call getEnvVar to retrieve information from Langfuse Observability without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves environment variables from a running Rails application via SSH, which is a read operation with no data modification. However, severity is elevated to medium because environment variables often contain sensitive information such as API keys, database credentials, and secrets that could be exploited if exposed to an untrusted AI agent, creating a potential information disclosure risk.
From the tool's definition Tool name 'getEnvVar' and description states 'Retrieve a specific environment variable' - a read-only operation that retrieves data with no side effects.
Attacks that exploit this kind of access
Retrieve a specific environment variable from your Rails application running on Hatchbox via SSH. This tool connects to your server and reads the requested environment variable directly from the running puma process. Example response: RAILS_ENV=production Or if not found: Environment variable. It is categorised as a Read tool in the Langfuse Observability MCP Server, which means it retrieves data without modifying state.
Register the Langfuse Observability MCP server in PolicyLayer and add a rule for getEnvVar: 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.
getEnvVar is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the getEnvVar 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 getEnvVar. 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.
getEnvVar 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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