Skip to main content
Glama

list-pods

Retrieve and filter active RunPod compute instances by GPU/CPU type, data center, name, and include machine or network volume details for management purposes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
computeTypeNoFilter to only GPU or only CPU Pods
dataCenterIdNoFilter to Pods in any of the provided data centers
gpuTypeIdNoFilter to Pods with any of the listed GPU types
includeMachineNoInclude information about the machine
includeNetworkVolumeNoInclude information about attached network volumes
nameNoFilter to Pods with the provided name

Implementation Reference

  • The handler function for the list-pods tool. It builds query parameters based on input filters and calls the RunPod API endpoint /pods to retrieve the list of pods, returning the JSON response as text content.
    async (params) => { // Construct query parameters const queryParams = new URLSearchParams(); if (params.computeType) queryParams.append('computeType', params.computeType); if (params.gpuTypeId) params.gpuTypeId.forEach((type) => queryParams.append('gpuTypeId', type)); if (params.dataCenterId) params.dataCenterId.forEach((dc) => queryParams.append('dataCenterId', dc) ); if (params.name) queryParams.append('name', params.name); if (params.includeMachine) queryParams.append('includeMachine', params.includeMachine.toString()); if (params.includeNetworkVolume) queryParams.append( 'includeNetworkVolume', params.includeNetworkVolume.toString() ); const queryString = queryParams.toString() ? `?${queryParams.toString()}` : ''; const result = await runpodRequest(`/pods${queryString}`); return { content: [ { type: 'text', text: JSON.stringify(result, null, 2), }, ], }; }
  • Zod schema defining the input parameters for the list-pods tool, including optional filters for compute type, GPU types, data centers, name, and inclusion flags.
    { computeType: z .enum(['GPU', 'CPU']) .optional() .describe('Filter to only GPU or only CPU Pods'), gpuTypeId: z .array(z.string()) .optional() .describe('Filter to Pods with any of the listed GPU types'), dataCenterId: z .array(z.string()) .optional() .describe('Filter to Pods in any of the provided data centers'), name: z .string() .optional() .describe('Filter to Pods with the provided name'), includeMachine: z .boolean() .optional() .describe('Include information about the machine'), includeNetworkVolume: z .boolean() .optional() .describe('Include information about attached network volumes'), },
  • src/index.ts:71-134 (registration)
    The server.tool call that registers the list-pods tool with its schema and handler function.
    server.tool( 'list-pods', { computeType: z .enum(['GPU', 'CPU']) .optional() .describe('Filter to only GPU or only CPU Pods'), gpuTypeId: z .array(z.string()) .optional() .describe('Filter to Pods with any of the listed GPU types'), dataCenterId: z .array(z.string()) .optional() .describe('Filter to Pods in any of the provided data centers'), name: z .string() .optional() .describe('Filter to Pods with the provided name'), includeMachine: z .boolean() .optional() .describe('Include information about the machine'), includeNetworkVolume: z .boolean() .optional() .describe('Include information about attached network volumes'), }, async (params) => { // Construct query parameters const queryParams = new URLSearchParams(); if (params.computeType) queryParams.append('computeType', params.computeType); if (params.gpuTypeId) params.gpuTypeId.forEach((type) => queryParams.append('gpuTypeId', type)); if (params.dataCenterId) params.dataCenterId.forEach((dc) => queryParams.append('dataCenterId', dc) ); if (params.name) queryParams.append('name', params.name); if (params.includeMachine) queryParams.append('includeMachine', params.includeMachine.toString()); if (params.includeNetworkVolume) queryParams.append( 'includeNetworkVolume', params.includeNetworkVolume.toString() ); const queryString = queryParams.toString() ? `?${queryParams.toString()}` : ''; const result = await runpodRequest(`/pods${queryString}`); return { content: [ { type: 'text', text: JSON.stringify(result, null, 2), }, ], }; } );
  • Shared helper function runpodRequest used by the list-pods handler (and other tools) to make authenticated HTTP requests to the RunPod API.
    async function runpodRequest( endpoint: string, method: string = 'GET', body?: Record<string, unknown> ) { const url = `${API_BASE_URL}${endpoint}`; const headers = { Authorization: `Bearer ${API_KEY}`, 'Content-Type': 'application/json', }; const options: NodeFetchRequestInit = { method, headers, }; if (body && (method === 'POST' || method === 'PATCH')) { options.body = JSON.stringify(body); } try { const response = await fetch(url, options); if (!response.ok) { const errorText = await response.text(); throw new Error(`RunPod API Error: ${response.status} - ${errorText}`); } // Some endpoints might not return JSON const contentType = response.headers.get('content-type'); if (contentType && contentType.includes('application/json')) { return await response.json(); } return { success: true, status: response.status }; } catch (error) { console.error('Error calling RunPod API:', error); throw error; } }

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/runpod/runpod-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server