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KN0WBOT

clavis-mcp-server

call_service

Securely call APIs with server-side credential injection, keeping API keys out of conversation. Prevents secret exposure and prompt-injection exfiltration.

Instructions

RECOMMENDED: Make an API call with server-side credential injection. The credential is fetched from the Clavis vault and injected into the upstream request server-side — the raw API key never enters this conversation. Prefer this over get_credentials: it eliminates prompt-injection exfiltration as an attack vector, because there is no secret in context to exfiltrate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL to call. Must be on the service connector's allowed domain — cross-domain URLs are rejected server-side (SSRF protection).
dataNoForm-encoded or raw body (mutually exclusive with json)
jsonNoJSON request body (mutually exclusive with data)
methodYesHTTP method for the upstream request
paramsNoURL query parameters
headersNoAdditional request headers. Auth headers are injected server-side and cannot be overridden.
service_nameYesName of the Clavis service whose credentials to inject (e.g. 'my-openai')
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the security model: the credential is fetched from Clavis vault and injected server-side, so the raw API key never enters the conversation. It also states that this prevents exfiltration, adding meaningful context beyond the 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?

The description is three sentences long, each serving a distinct purpose: stating the action, explaining the credential handling, and providing usage guidance. It is front-loaded with 'RECOMMENDED' and wastes no words.

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?

The description covers the tool's purpose, security behavior, and preferred usage, while the schema exhaustively documents parameters. Although there is no output schema and the description doesn't explicitly state the return format, the tool is an API caller so the response is presumably the upstream response; this is a minor gap given the overall context.

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?

Schema description coverage is 100%, so the schema fully documents each parameter. The description reinforces the purpose of service_name (credential injection) but doesn't add new parameter-level details beyond what the schema already provides, earning the baseline score.

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 function: 'Make an API call with server-side credential injection.' It names the specific resource (Clavis vault credentials) and distinguishes itself from sibling tool get_credentials, so there is no ambiguity about what this tool does.

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

Usage Guidelines5/5

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

Explicit guidance is provided: 'Prefer this over get_credentials' with a rationale that it eliminates prompt-injection exfiltration. The 'RECOMMENDED' label further signals preferred usage over the alternative.

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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