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sanjaypsachdev

OpenShift MCP Server

oc_login

Log into an OpenShift cluster using username/password or token authentication to enable subsequent cluster management operations.

Instructions

Securely log into an OpenShift cluster using username/password or token authentication

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenNoOpenShift authentication token (required if authMethod is token)
serverYesOpenShift cluster server URL (e.g., https://api.cluster.example.com:6443)
contextNoContext name to save the login session (optional)
timeoutNoLogin timeout in seconds
passwordNoPassword for password authentication (required if authMethod is password)
usernameNoUsername for password authentication (required if authMethod is password)
namespaceNoDefault namespace to set after logindefault
authMethodYesAuthentication method to usetoken
certificateAuthorityNoPath to certificate authority file for TLS verification
insecureSkipTlsVerifyNoSkip TLS certificate verification (not recommended for production)
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions 'securely' but does not disclose side effects such as modifying kubeconfig, persisting credentials, changing the current context, or requiring network access to the cluster. This is a notable gap for a login tool that changes state.

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, concise sentence that front-loads the core action and auth methods, with no filler words. It is appropriately sized.

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?

The tool has 10 parameters and no output schema or annotations, yet the description only covers the basic login action. It omits important context like the effect on the local kubeconfig, the need for network access to the server, and how login interacts with other oc tools. This is insufficient for an AI agent to fully understand usage and consequences.

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?

The schema already provides detailed descriptions for all 10 parameters, including conditional requirements (required if authMethod is token/password). The description adds no additional parameter-level meaning beyond restating the auth methods, so it does not improve on the schema.

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 the tool's action (log into) and resource (OpenShift cluster), and explicitly lists the authentication methods (username/password or token). This distinguishes it from sibling tools like oc_get or oc_apply, which perform cluster operations rather than authentication.

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

Usage Guidelines3/5

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

The description implies that this tool is a prerequisite for other oc commands but does not explicitly state when to use it or when not to use it, nor does it mention alternatives. There is no guidance about requiring an existing cluster connection or how it fits into a workflow.

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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