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volume_create

Create persistent storage volumes for Railway services to manage database files, application data, and other storage needs that require data retention across deployments.

Instructions

[API] Create a new persistent volume for a service

⚡️ Best for: ✓ Setting up database storage ✓ Configuring persistent data ✓ Adding file storage

⚠️ Not for: × Temporary storage needs × Static file hosting × Memory caching

→ Prerequisites: service_list

→ Next steps: volume_list

→ Related: service_update, database_deploy

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesID of the project containing the service
environmentIdYesID of the environment for the volume (usually obtained from service_info)
serviceIdYesID of the service to attach volume to
mountPathYesPath where the volume should be mounted in the container

Implementation Reference

  • The handler function for the 'volume_create' tool, which delegates to volumeService.createVolume.
    async ({ projectId, environmentId, serviceId, mountPath }) => {
      return volumeService.createVolume(projectId, serviceId, environmentId, mountPath);
    }
  • Zod input schema defining parameters for the volume_create tool.
    {
      projectId: z.string().describe("ID of the project containing the service"),
      environmentId: z.string().describe("ID of the environment for the volume (usually obtained from service_info)"),
      serviceId: z.string().describe("ID of the service to attach volume to"),
      mountPath: z.string().describe("Path where the volume should be mounted in the container")
    },
  • Local registration of the volume_create tool within the volumeTools array using createTool.
    createTool(
      "volume_create",
      formatToolDescription({
        type: 'API',
        description: "Create a new persistent volume for a service",
        bestFor: [
          "Setting up database storage",
          "Configuring persistent data",
          "Adding file storage"
        ],
        notFor: [
          "Temporary storage needs",
          "Static file hosting",
          "Memory caching"
        ],
        relations: {
          prerequisites: ["service_list"],
          nextSteps: ["volume_list"],
          related: ["service_update", "database_deploy"]
        }
      }),
      {
        projectId: z.string().describe("ID of the project containing the service"),
        environmentId: z.string().describe("ID of the environment for the volume (usually obtained from service_info)"),
        serviceId: z.string().describe("ID of the service to attach volume to"),
        mountPath: z.string().describe("Path where the volume should be mounted in the container")
      },
      async ({ projectId, environmentId, serviceId, mountPath }) => {
        return volumeService.createVolume(projectId, serviceId, environmentId, mountPath);
      }
    ),
  • Global registration of all tools, including volumeTools which contains volume_create, to the MCP server.
    export function registerAllTools(server: McpServer) {
      // Collect all tools
      const allTools = [
        ...databaseTools,
        ...deploymentTools,
        ...domainTools,
        ...projectTools,
        ...serviceTools,
        ...tcpProxyTools,
        ...variableTools,
        ...configTools,
        ...volumeTools,
        ...templateTools,
      ] as Tool[];
    
      // Register each tool with the server
      allTools.forEach((tool) => {
        server.tool(
          ...tool
        );
      });
    } 
  • Service layer implementation that handles volume creation logic, error handling, and response formatting by calling the client.
    async createVolume(projectId: string, serviceId: string, environmentId: string, mountPath: string): Promise<CallToolResult> {
      try {
        const input = { projectId, serviceId, environmentId, mountPath };
    
        const volume = await this.client.volumes.createVolume(input);
        if (!volume) {
          return createErrorResponse(`Error creating volume: Failed to create volume for ${serviceId} in environment ${environmentId}`);
        }
        
        return createSuccessResponse({
          text: `✅ Volume "${volume.name}" created successfully (ID: ${volume.id})`,
          data: volume
        });
      } catch (error) {
        return createErrorResponse(`Error creating volume: ${formatError(error)}`);
      }
    }
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the volume is 'persistent' and for a 'service', which adds some context about the tool's behavior. However, it lacks details on permissions, error handling, or what the tool returns, leaving gaps in behavioral transparency for a creation tool with no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by bullet-pointed sections for best uses, exclusions, prerequisites, next steps, and related tools. Each sentence or bullet point adds value without redundancy, making it efficient and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity as a creation operation with no annotations and no output schema, the description provides strong usage guidelines and related tool context. However, it lacks details on behavioral aspects like return values or error conditions, which slightly reduces completeness. The high schema coverage and clear structure compensate partially, but not fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the input schema already documents all four parameters (projectId, environmentId, serviceId, mountPath) with descriptions. The description does not add any parameter-specific details beyond what the schema provides, such as format examples or constraints, resulting in a baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Create' and resource 'new persistent volume for a service', making the purpose specific and unambiguous. It distinguishes this tool from sibling tools like volume_list, volume_update, and volume_delete by focusing on creation rather than listing, updating, or deleting volumes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance with 'Best for' and 'Not for' sections, clearly indicating when to use this tool (e.g., for database storage, persistent data) and when not to use it (e.g., for temporary storage, static file hosting). It also lists prerequisites (service_list), next steps (volume_list), and related tools (service_update, database_deploy), offering comprehensive usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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