runpod-mcp
Manage Runpod infrastructure — pods, serverless endpoints, jobs, templates, network volumes, container-registry auth, GPU/CPU catalog, and billing — via the Runpod MCP server's structured tool calls. Use when the Runpod MCP tools (create-pod, list-endpoints, …) are connected in this session, or to connect them (hosted OAuth or local npx). Prefer this over runpodctl for plain infra CRUD when MCP is available; use runpodctl for the terminal, file transfer, or SSH setup.
How do I install this agent skill?
npx skills add https://github.com/runpod/runpod-plugins-official --skill runpod-mcpIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill facilitates infrastructure management for Runpod via their official Model Context Protocol (MCP) server. It uses standard authentication methods and official vendor packages for its functionality.
- Socketpass
No alerts
- Snykwarn
Risk: MEDIUM · 1 issue
What does this agent skill do?
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).
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:
printf '%s\n' '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"probe","version":"0"}}}' \
| curl -s -X POST https://mcp.getrunpod.io/ -H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" -H "Authorization: Bearer $RUNPOD_API_KEY" -d @-
# → serverInfo.version e.g. "3.0.0 [RUNPOD_REST_VERSION=v2]" (verified 2026-07-29)
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.
create-endpointtakesendpointType: QUEUE(default) orLOAD_BALANCER— see golden path 14. The routing type is fixed at creation;update-endpointcannot change it.- Read an endpoint's invoke URLs from
requestUrlson 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-endpointexpose onlygpuPoolIdsand can't express a SKU (deploy-hub-repocan pin one at deploy time viagpuIdsexclusions).
- 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, …) anddeploy-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 withrun-endpoint/runsync-endpoint. - Templates — list, get, create, update, delete.
- Network volumes — list, get, create, update, delete.
create-network-volumetakesvolumeType(STANDARD|HIGH_PERFORMANCE) and a size of 10–4096 GB; omitvolumeTypeto get the data center's default tier. The tier is immutable after creation —update-network-volumecan't change it. - Container registry auth — list, get, create, delete. A username + password for any registry; pass the resulting id as
containerRegistryAuthIdon 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 adockerRegistryUri— 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 returnisError: truewith "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-upget-/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/receivefile transfer, SSH key management,doctorsetup, 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
gpuTypeIdsare dropped with a_warningon success), or for a template + CPU pod together —create-podrejects that combination, since a template deploy is GPU-and-v2-only. Each alone is fine in MCP:templateId(v2-only,imageNamethen optional, and each field you pass replaces the template's whole value rather than merging) orcomputeType: "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
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/runpod/runpod-plugins-official/runpod-mcp">View runpod-mcp on skillZs</a>