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Get an API key with free credits

create_api_key

Start here if you do not have an AIDataParser API key. Provide the user's email and receive a live adp_live_ API key with 50 free credits — no card, no signup form. Configure it on this MCP server as Authorization: Bearer <api_key> to unlock parse_document, parse_text and infer_schema. The key is returned ONCE and is never shown again, so surface it to the user and store it. Ask the user for their address; do not invent one. Free — does not consume a credit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe user's email address. The account and its free credits belong to this address; an address that already has an account is refused rather than issued a second key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

The description goes well beyond the annotations (all false) by disclosing that the key is returned once and never shown again, instructing the agent to ask the user for their address, and stating the operation is free and does not consume credits. This is rich behavioral context that annotations do not provide.

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 well-structured and front-loaded with the condition, then explains the result, behavioral caveats, and configuration. Each sentence earns its place with no redundant or filler content.

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?

For a single-parameter tool with no output schema, the description captures everything an agent needs: the one-time return, the need to store it, the address request, and the configuration instructions. It is fully self-contained.

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?

The schema already provides 100% coverage for the email parameter, describing account ownership and refusal for duplicate addresses. The description reinforces the need to provide the user's email and adds an actionable agent instruction ('Ask the user for their address'), which adds value beyond the schema but does not introduce new parameter semantics.

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 tool as the entry point for obtaining an API key when none exists. It states the verb (get/create), the resource (adp_live_ API key with 50 free credits), and differentiates from siblings by explaining it unlocks parse_document, parse_text, and infer_schema.

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?

The description provides an explicit condition: 'Start here if you do not have an AIDataParser API key.' It also gives practical steps (provide email, configure as Bearer token) and notes the free cost, making it clear when and how to use the tool.

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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