list_reservations
Lists Compute Engine reservations. Details for each reservation include name, ID, creation timestamp, zone, status, specific reservation required, commitment, and linked commitments. Requires project and zone as input.
This record as markdown: /tools/com-googleapis-compute-mcp/list-reservations.md
What list_reservations does on Mcp
AI agents call list_reservations to retrieve information from Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
zone | string | Yes | Required. The zone of the reservations. |
project | string | Yes | Required. Project ID for this request. |
pageSize | integer | — | Optional. The maximum number of reservations to return. |
pageToken | string | — | Optional. A page token received from a previous call to list reservations. |
Parameters from the server's own tool schema.
Why list_reservations is rated Low
The tool retrieves and queries reservation metadata without any side effects. It takes project and zone as input parameters and returns informational data about reservations. This is a classic Read operation—no data is created, modified, deleted, or executed. The blast radius of misuse is minimal (information disclosure only), warranting low severity.
From the tool's definition Tool description states it 'Lists Compute Engine reservations' and 'Details for each reservation include name, ID, creation timestamp, zone, status, specific reservation required, commitment, and linked commitments.' This is a read-only query operation with…
Attacks that exploit this kind of access
The rule that runs list_reservations safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For list_reservations, this is the rule to start with:
list_reservations is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp, apply this rule, and every list_reservations call is checked against it from then on.
Questions about list_reservations
Lists Compute Engine reservations. Details for each reservation include name, ID, creation timestamp, zone, status, specific reservation required, commitment, and linked commitments. Requires project and zone as input. It is categorised as a Read tool in the Mcp MCP Server, which means it retrieves data without modifying state.
list_reservations accepts 4 parameters: zone, project, pageSize, pageToken. Required: zone, project. The full parameter table on this page comes from the server's own tool schema.
Register the MCP server in PolicyLayer and add a rule for list_reservations: 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 Mcp. Nothing to install.
list_reservations 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 list_reservations 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 list_reservations. 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.
list_reservations is provided by the MCP server (https://compute.googleapis.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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