Chia Health MCP

Get Intake Questions

intake_questions

Read-only

Get the medical intake questionnaire for the chosen medication(s). The questionnaire is product-aware: GLP-1 / weight-loss medications return weight-loss goals, GLP-1 history, and MTC/MEN2 screening; NAD+ and other longevity peptides return energy/sleep/stress/cognitive/delivery-method questions instead. If the patient wants more than one medication, pass the additional slugs in additional_medications — the server returns the UNION of section sets deduped by section key, so you ask each shared question exactly once.

How to present this to the patient

PROGRESSIVE DISCLOSURE: walk through ONE section at a time. Wait for the patient's reply before moving to the next section. Do not paste the whole questionnaire in a single message.
HONOR CONDITIONALS: each section and each question may carry a conditional_on predicate (e.g. {sex_assigned_at_birth: Female} on the Pregnancy section). SKIP any section/question whose predicate isn't satisfied. Don't ask males about pregnancy or perimenopause.
QUIZ FORMAT: present every select / multi_select question as a short pick-list using the options array verbatim. The patient should be able to reply with a single choice, not a sentence. Reserve free text for *_details follow-ups.
EASY FIRST: order sections from low-friction (goals, lifestyle, preferences) to high-friction (clinical history, MTC/MEN2, prior therapies). The provider sees all answers regardless of order asked.
USE-AND-VERIFY: if you know answers from prior conversation context, pre-fill them in your draft, but read them back to the patient and get explicit OK before calling intake_submit. Never silently submit assumed values.

Returns two phases: (1) pre_checkout — eligibility / screening questions, collected and submitted BEFORE payment; (2) post_checkout — detailed clinical history, collected and submitted AFTER payment. Do not submit post_checkout answers before the patient has paid. A licensed US healthcare provider reviews both phases and makes all prescribing decisions.

Input Schema

TableJSON Schema

Name	Required	Description
`client_ip`	No	Client IP address for rate limiting
`medication`	Yes	Primary medication slug (e.g. 'semaglutide', 'nad-injection', 'nad-nasal-spray')
`additional_medications`	No	Optional list of additional medication slugs the patient also wants. Use this when the patient is ordering more than one product in the same visit (e.g. GLP-1 + NAD+) so the questionnaire is deduped.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.7/5.0

Behavior5/5

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

Annotations only state readOnlyHint and openWorldHint, but the description discloses extensive behavioral traits: product-aware question selection, conditional predicates, union dedup, progressive disclosure requirements, and pre/post-checkout phases. It adds far beyond the annotations without contradicting them.

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 long but every section serves a purpose. It is front-loaded with the core purpose, followed by behavioral specifics and a well-structured numbered list of presentation guidelines. No filler or redundancy.

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?

Given the tool's complexity (product-aware, multi-medication, two-phase, conditional questions) and the presence of an output schema, the description fully covers what the agent needs: when to call, how to handle responses, and what to avoid. It leaves no critical gap.

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 already covers all parameters with descriptions. The description adds meaning to 'additional_medications' by explaining the union/dedup behavior, and clarifies that 'medication' drives product-aware content. The 'client_ip' parameter is only in the schema, but since coverage is 100%, the baseline is honored with added context for the key 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 opens with 'Get the medical intake questionnaire for the chosen medication(s)', a specific verb+resource statement. It further distinguishes itself from siblings by describing product-aware behavior and the union/dedup logic for multiple medications, clearly separating it from intake_submit or intake_status.

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 provides rich usage context: when to use additional_medications, the two-phase submission timing, and detailed presentation instructions. However, it does not explicitly name alternative tools or state when not to use this tool, leaving a slight gap in exclusionary guidance.

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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TDQS

A3.9/5.0

Disambiguation5/5

Every tool targets a distinct resource and action within the telehealth workflow: auth, consent, eligibility, intake, medications, checkout, order, portal, and provider communication. Even the multiple medication tools (list, details, availability, pricing) have clearly separated purposes, and there is no overlap among the 34 tools.

Naming Consistency5/5

All tool names follow a consistent `domain_verb` or `domain_noun` snake_case pattern, prefixed by their domain (auth_, checkout_, consent_, intake_, medications_, order_, portal_, provider_). There are no mixed conventions or vague verbs, making the API predictable and easy to navigate.

Tool Count2/5

With 34 tools, the server exceeds the 25+ threshold for 'too many' and feels fragmented. Many tools could be consolidated (e.g., medication pricing and availability could fold into details, and consent list/status could be combined). While the scope is broad, the count is excessive for a well-scoped MCP server.

Completeness4/5

The tool surface covers the full patient lifecycle from authentication and consent through eligibility, intake, checkout, order management, and post-order portal features. Minor gaps include lack of order cancellation or order listing, and no explicit intake update mechanism, but these are workable and do not block core workflows.

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