runpod-mcp

Runpod MCP

The Runpod MCP server exposes Runpod's control plane as structured tool calls, so an MCP-capable agent can manage infrastructure without shelling out. It is the same Runpod REST API that runpodctl uses — pick MCP when its tools are connected (typed params, structured errors, no shell quoting).

For a multi-step job, read the worked example before calling tools. Tool calls are easy to issue and easy to issue in the wrong order — the verified end-to-end sequences live in runpod/golden-paths/README.md (image → template → endpoint, pod → volume → serverless, multi-region, autoscaling, monitoring). This skill covers what each tool does; the paths cover what order to do them in and what it costs.

Connect

Connect the hosted server with your API key as a Bearer header if you also use runpodctl/flash — that one key auths the MCP and the CLIs (the 80% path):

claude mcp add --transport http runpod -s user https://mcp.getrunpod.io/ \
  --header "Authorization: Bearer $RUNPOD_API_KEY"

Plain OAuth ("Sign in with Runpod", via npx @runpod/mcp-server@latest add) is MCP-only — the CLIs stay unauthed, so use it only for MCP-only work. Local stdio runs the server as a subprocess with your key. Those variants + the key-vs-OAuth tradeoff: reference/connect.md. After connecting, reconnect the client (in Claude Code, /mcp) so the tools load.

Verify it's live (do this before relying on MCP): in Claude Code run /mcp — runpod should show Connected, not Needs authentication (if it's the latter, sign in there first; the bundled plugin server registers the URL but stays inert until you authenticate). Confirm a real call works by asking for list-endpoints. If the runpod tools aren't present at all, the server isn't connected — (re)run the install above, or fall back to runpodctl for this task.

Check the server version (which REST API it drives): the MCP initialize handshake returns it in serverInfo.version. /mcp in Claude Code shows it, or probe the hosted server directly:

The MCP server drives Runpod's REST v2 internally (RUNPOD_REST_VERSION=v2), so most tools avoid the buggy public rest.runpod.io/v1 control API. Two exceptions worth knowing: the Hub, public-endpoint and set-endpoint-gpus tools go through GraphQL (so they work under either REST version), and CPU serverless endpoints are not creatable through MCP — v2 has no CPU-endpoint concept at all (create-endpoint requires gpuPoolIds), so use runpodctl serverless create --compute-type CPU for those.

Prefer MCP or runpodctl over hand-rolled rest.runpod.io/v1 calls for creating endpoints.

Tool surface

Structured tools, grouped by resource:

• Pods — list, get, create, update, start, stop, restart, delete, stream logs.
• Serverless endpoints — list, get, create, update, delete; list workers; list releases; stream worker logs.
  • Logs are no longer an MCP-only capability — runpodctl grew pod logs and serverless logs in v2.10.0. MCP still returns already-parsed, bounded frames, which is the easier shape inside an agent; reach for the CLI when you are shell-only or want --follow. Job output streaming (stream-job) remains MCP-only.
  • create-endpoint takes endpointType: QUEUE (default) or LOAD_BALANCER — see golden path 14. The routing type is fixed at creation; update-endpoint cannot change it.
  • Read an endpoint's invoke URLs from requestUrls on the get/list reply instead of assembling them.
  • To pin a specific GPU SKU on an existing endpoint use set-endpoint-gpus; create-endpoint/update-endpoint expose only gpuPoolIds and can't express a SKU (deploy-hub-repo can pin one at deploy time via gpuIds exclusions).
• Jobs (serverless runtime) — run, runsync, status, stream, cancel, retry, health, purge queue.
• Hub — list-hub-repos (public catalog of prebuilt Serverless workers and Pod templates: vLLM, ComfyUI, …) and deploy-hub-repo, which deploys a repo's listed release as an endpoint — the same as clicking Deploy on the Hub.
• Public endpoints — list-public-endpoints: managed pay-per-use model APIs (text/image/video/audio) that need no deployment. Call the returned endpointId with run-endpoint/runsync-endpoint.
• Templates — list, get, create, update, delete.
• Network volumes — list, get, create, update, delete. create-network-volume takes volumeType (STANDARD | HIGH_PERFORMANCE) and a size of 10–4096 GB; omit volumeType to get the data center's default tier. The tier is immutable after creation — update-network-volume can't change it.
• Container registry auth — list, get, create, delete. A username + password for any registry; pass the resulting id as containerRegistryAuthId on create-pod/create-endpoint.
• ECR delegations (list-/create-/delete-registry-delegation) — AWS ECR only, v2 only, and stores no credentials: you register a repository ARN and Runpod gets scoped pull access instead. Prefer it over a stored username/password for ECR. The reply carries a dockerRegistryUri — that's the image URI to deploy with.
• Catalog — list/get GPU types, list/get CPU types, list/get data centers.
• Billing — scoped usage/cost breakdowns (get-billing).

The tool list above is a map, not a contract. The server is the source of truth — /mcp (or your client's tool list) shows exactly what the connected version exposes, and each tool carries its own parameter descriptions. Check there before assuming a capability exists or doesn't.

Delete tools (delete-template, delete-pod, …) can return isError: true with "Unexpected end of JSON input" even on success — the Runpod REST API returns 204 No Content. Don't treat it as failure; confirm with a follow-up get-/list- (a deleted resource then 404s).

Use MCP vs runpodctl

• Use runpod-mcp when the tools are connected AND the task is infra CRUD or a serverless job call the server exposes. Cap large job/log output to a file.
• Use runpodctl instead for: send/receive file transfer, SSH key management, doctor setup, model cache — or any shell-only agent, or when the user wants a reproducible command.
• Hand pod creation to runpodctl for a multi-GPU priority list (MCP's v2 create-pod takes one GPU type; extra gpuTypeIds are dropped with a _warning on success), or for a template + CPU pod together — create-pod rejects that combination, since a template deploy is GPU-and-v2-only. Each alone is fine in MCP: templateId (v2-only, imageName then optional, and each field you pass replaces the template's whole value rather than merging) or computeType: "CPU".
• Not this lane: writing/deploying your own Python (→ flash); downloading models or building/pushing images (→ companion-clis).

For concepts (pods vs serverless, GPU selection, storage), read ../runpod-usage/.

Source & docs

• Server source: https://github.com/runpod/runpod-mcp
• Package (npm): https://www.npmjs.com/package/@runpod/mcp-server
• Hosted endpoint: https://mcp.getrunpod.io/
• Docs: https://docs.runpod.io