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HyperRouteAI

hyperroute-mcp

Official
by HyperRouteAI

onboard

Save a tool API key once so HyperRoute can run that tool for you on every future execute.

Instructions

Save ONE tool API key under the logged-in account so HyperRoute runs that tool for the user on every future execute — onboard once, reuse forever. The key is stored encrypted at rest and tested against the tool's identity endpoint before it's kept (a rejected key is not saved). It never leaves the server: HyperRoute uses it to run the tool and returns only the result. Get the key from the user first — see connect_info for where they obtain it. Requires login.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelNo
api_keyYes
tool_idYes
Behavior5/5

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

With no annotations, the description carries the full burden and excels: it discloses encryption at rest, validation against the tool's identity endpoint (rejected keys not saved), server-side key handling, persistence across future `execute` calls, and login requirement. This is exactly the behavioral detail needed beyond schema.

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?

Four sentences, each contributing unique value: purpose, storage/validation, server-side behavior, and user instruction. No redundancy or fluff; the critical details are front-loaded in the first sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no annotations and no output schema, the description fully covers the tool's purpose, prerequisites (login, user-provided key), key lifecycle (encrypted, validated, rejected if invalid), and operational implications (persistence, server-side use). It even references `connect_info` for key acquisition. No major information gaps remain.

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

Parameters2/5

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

Schema coverage is 0%, and the description only alludes to the api_key ('the key') without explicitly mapping to parameter names. It does not mention `tool_id` or `label` at all, so it fails to compensate for the missing schema documentation. The agent would need to infer tool_id from context, which is insufficient.

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 identifies the action ('Save ONE tool API key under the logged-in account') and the resource (tool API key). It distinguishes the tool from siblings like `connect_info` (which provides info) and `execute` (which runs tools) by emphasizing the one-time onboarding and future reuse.

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?

Provides concrete usage context: requires login, get the key from the user first, and points to `connect_info` as a reference for where the key is obtained. While it doesn't explicitly list when not to use the tool or name alternative tools, the context is sufficient for an agent to decide when to invoke it.

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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