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railwayapp

Railway MCP Server

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by railwayapp

Set Railway Variables

set-variables

Set environment variables for the active environment in Railway projects to configure application settings and manage deployment configurations.

Instructions

Set environment variables for the active environment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspacePathYesThe path to the workspace to set variables in
variablesYesArray of '{key}={value}' environment variable pairs to set
serviceNoThe service to set variables for (optional)
environmentNoThe environment to set variables for (optional)
skipDeploysNoSkip triggering deploys when setting variables (optional)

Implementation Reference

  • The asynchronous handler function for the 'set-variables' tool that invokes setRailwayVariables with provided options, wraps the result in createToolResponse, and provides detailed error handling with next steps.
    handler: async ({
    	workspacePath,
    	variables,
    	service,
    	environment,
    	skipDeploys,
    }: SetVariablesOptions) => {
    	try {
    		const result = await setRailwayVariables({
    			workspacePath,
    			variables,
    			service,
    			environment,
    			skipDeploys,
    		});
    
    		return createToolResponse(result);
    	} catch (error: unknown) {
    		const errorMessage =
    			error instanceof Error ? error.message : "Unknown error occurred";
    		return createToolResponse(
    			"❌ Failed to set Railway variables\n\n" +
    				`**Error:** ${errorMessage}\n\n` +
    				"**Next Steps:**\n" +
    				"• Ensure you have a Railway project linked\n" +
    				"• Check that the service and environment exist\n" +
    				"• Verify you have permissions to set variables\n" +
    				"• Ensure variable format is correct (KEY=value)\n" +
    				"• Run `railway link` to ensure proper project connection",
    		);
    	}
    },
  • Zod schema defining the input parameters for the 'set-variables' tool: workspacePath, variables array, optional service, environment, and skipDeploys.
    inputSchema: {
    	workspacePath: z
    		.string()
    		.describe("The path to the workspace to set variables in"),
    	variables: z
    		.array(z.string())
    		.describe("Array of '{key}={value}' environment variable pairs to set"),
    	service: z
    		.string()
    		.optional()
    		.describe("The service to set variables for (optional)"),
    	environment: z
    		.string()
    		.optional()
    		.describe("The environment to set variables for (optional)"),
    	skipDeploys: z
    		.boolean()
    		.optional()
    		.describe("Skip triggering deploys when setting variables (optional)"),
    },
  • src/index.ts:21-31 (registration)
    Dynamic registration of all exported tools (including 'set-variables') to the MCP server using server.registerTool with name, schema, and handler.
    Object.values(tools).forEach((tool) => {
    	server.registerTool(
    		tool.name,
    		{
    			title: tool.title,
    			description: tool.description,
    			inputSchema: tool.inputSchema,
    		},
    		tool.handler,
    	);
    });
  • Helper function that constructs and executes the 'railway variables --set KEY=value ...' CLI command, checks project linkage, handles errors, and returns output.
    export const setRailwayVariables = async ({
    	workspacePath,
    	variables,
    	service,
    	environment,
    	skipDeploys,
    }: SetVariablesOptions): Promise<string> => {
    	try {
    		await checkRailwayCliStatus();
    		const result = await getLinkedProjectInfo({ workspacePath });
    		if (!result.success) {
    			throw new Error(result.error);
    		}
    
    		let command = "railway variables";
    
    		if (service) {
    			command += ` --service ${service}`;
    		}
    		if (environment) {
    			command += ` --environment ${environment}`;
    		}
    		if (skipDeploys) {
    			command += " --skip-deploys";
    		}
    
    		// Add each variable with --set flag
    		variables.forEach((variable) => {
    			command += ` --set "${variable}"`;
    		});
    
    		const { output } = await runRailwayCommand(command, workspacePath);
    		return output;
    	} catch (error: unknown) {
    		return analyzeRailwayError(error, "railway variables --set");
    	}
    };
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool sets environment variables, implying a write/mutation operation, but doesn't mention critical behaviors like whether this requires specific permissions, if changes are reversible, potential side effects (e.g., triggering deploys), or rate limits. This is inadequate for a mutation tool with zero annotation coverage.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly while conveying the essential action and target.

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

Completeness2/5

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

Given the tool's complexity (mutation operation with 5 parameters) and lack of both annotations and output schema, the description is insufficient. It doesn't explain what happens after setting variables (e.g., success/failure responses, whether deploys are triggered by default), leaving significant gaps for an AI agent to understand the tool's full behavior and outcomes.

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?

Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as examples or constraints not captured in structured fields. This meets the baseline for high schema coverage but doesn't provide extra value.

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

Purpose4/5

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

The description clearly states the action ('Set') and resource ('environment variables for the active environment'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'list-variables' or 'create-environment', which could help with similar operations in the Railway context.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'list-variables' for checking existing variables or 'create-environment' for environment setup. It mentions 'active environment' but doesn't clarify prerequisites or contextual constraints, leaving usage scenarios ambiguous.

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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