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Chia Health MCP Server

Submit Consent

consent_submit
DestructiveIdempotent

Record a patient's consent confirmation for a specific consent document. The agent must have already presented the full consent text (from consent_text) to the patient and received explicit confirmation. Required parameters: intake_id, consent_id, the patient's exact confirmation text (e.g. 'I agree'), consent method ('ai_agent_conversational'), the AI platform name ('chatgpt', 'claude', 'gemini'), and a session/conversation ID for audit trail. Returns a consent record with timestamp, audit trail details, and the list of remaining consents still needed. All consent records are retained for 10 years per HIPAA requirements. Requires authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intake_idYesIntake ID this consent belongs to
timestampNoISO 8601 timestamp of consent confirmation
consent_idYesConsent document ID being confirmed
bearer_tokenNoAuthentication token for the patient session
agent_platformNoAI platform name: 'chatgpt', 'claude', or 'gemini'
consent_methodNoMethod of consent collectionai_agent_conversational
agent_session_idNoUnique session/conversation ID for audit trail
patient_confirmationYesPatient's exact confirmation text (e.g. 'I agree')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.1/5.0
Behavior4/5

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

With annotations already indicating write, idempotent, and destructive hints, the description adds valuable behavioral context: HIPAA-mandated 10-year retention, requirement for exact confirmation text, audit trail details, and authentication requirement. It does not contradict any annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately structured but contains an unnecessary and incorrect enumeration of required parameters that conflicts with the schema. While the core purpose, prerequisite, and retention info are useful, the parameter list wastes space and adds confusion.

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 purpose, prerequisite, return value (consent record with timestamp and remaining consents), retention, and authentication. Combined with the output schema and annotations, it is quite comprehensive. However, the parameter required-list error is a notable completeness gap.

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?

The schema already provides full coverage of all 8 parameters with descriptions (100% coverage). However, the description incorrectly lists more parameters as required than the schema marks as required (only intake_id, consent_id, patient_confirmation are required; consent_method, agent_platform, agent_session_id are optional). This misleading information degrades the 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 states the tool records a patient's consent confirmation for a specific consent document, with a specific verb ('record') and resource. It distinguishes itself from siblings like consent_text (provides text) and consent_list/status (read consent data) by focusing on the submission action.

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 explicitly states the prerequisite: the agent must have already presented the full consent text from consent_text and received explicit confirmation. This provides clear guidance on when to use this tool and references the sibling tool for the prior step.

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

A4.2/5.0
Disambiguation4/5

Most tools have distinct purposes with clear boundaries, such as auth_* for authentication, checkout_* for payment, and portal_* for patient portal actions. However, there is some overlap between checkout_status and auth_check_payment (both involve polling for payment status) and between portal_support and portal_message (both for communication), which could cause minor confusion.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun pattern throughout, with clear prefixes grouping related tools (e.g., auth_, checkout_, consent_, intake_, medications_, order_, portal_, provider_). This predictable structure makes it easy to understand the tool set's organization and purpose.

Tool Count3/5

With 34 tools, the count is borderline high for a telehealth server, as it may feel heavy and complex for agents to navigate. While the tools cover a comprehensive workflow from authentication to patient portal, some consolidation (e.g., merging similar polling tools) could improve usability without losing functionality.

Completeness5/5

The tool set provides complete coverage for the telehealth domain, including authentication, eligibility checks, medication browsing, intake, consent, checkout, order management, and patient portal features. There are no obvious gaps; agents can handle the entire patient journey from start to ongoing care without dead ends.