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RunPod MCP Server

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by runpod

update-endpoint

Idempotent

Update configuration of a RunPod serverless endpoint. Modify fields like image, workers, scaling, or environment variables without affecting unmentioned settings.

Instructions

Update a Serverless endpoint's config. On v2 you can change image/disk/env/ports/registry/workers/scaling/networkVolumes/timeout/flashboot; on v1, scaling fields (worker min/max, idle timeout, scaler type/value, name). Only provided fields change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNoNew environment variables (v2)
argsNoNew container args (v2)
nameNoNew name for the endpoint
portsNoNew ports (v2)
gpuCountNoNew GPUs per worker (v2)
flashbootNoNew FlashBoot mode (v2)
imageNameNoNew Docker image (v2)
endpointIdYesID of the endpoint to update
gpuPoolIdsNoNew GPU pool names (v2), e.g. ["AMPERE_80"]
scalerTypeNoScaler type
workersMaxNoNew maximum number of workers
workersMinNoNew minimum number of workers
idleTimeoutNoNew idle timeout in seconds
scalerValueNoScaler value
networkVolumeIdsNoNew network volume ids (v2)
containerDiskInGbNoNew container disk size in GB (v2)
executionTimeoutMsNoNew per-job execution timeout in ms (v2)
containerRegistryAuthIdNoNew container registry auth id (v2)
Behavior5/5

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

Annotations provide idempotentHint=true, and the description adds crucial behavioral details: 'Only provided fields change' (partial update semantics) and version-specific field lists. No contradiction with annotations.

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?

Two sentences, front-loaded with purpose, and efficiently conveys version split and partial update behavior. Every sentence earns its place.

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?

For a mutation tool with 18 parameters and no output schema, the description covers the key behavioral aspects and parameter groupings. It does not address potential conflicts between v1 and v2 parameter mixing, but overall is adequate.

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

Parameters4/5

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

Schema description coverage is 100%, but the description adds value by grouping parameters into v2 and v1 categories, which is not present in the schema. This helps the agent select appropriate parameters.

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 it updates a Serverless endpoint's config, distinguishing between v2 and v1 capabilities. The verb 'Update' and resource 'Serverless endpoint' are specific, and the listing of changable fields differentiates it from create-endpoint.

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

Usage Guidelines4/5

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

The description implies usage for modifying an existing endpoint, but does not explicitly contrast with create or delete siblings. It does provide clear context on which fields apply to v2 vs v1, aiding correct invocation.

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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