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intakeq

Create or update a client

intakeq_save_client
Destructive

Create a client, or update one. With ClientId the existing client is updated. WITHOUT ClientId IntakeQ still tries to match an existing client by first name + email (or first name + phone) and updates that one instead of creating a duplicate. For updates, fetch the full profile first (intakeq_list_clients with include_profile=true) and send it back with your changes, so no field is unintentionally cleared. Field names are IntakeQ's own. Dates are Unix timestamps in milliseconds. IntakeQ: POST /clients.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
CityNo
NameNoFull name.
EmailNo
PhoneNo
GenderNo
AddressNoFull address, or send the components below instead.
CountryNo
ArchivedNo
ClientIdNoUpdate this existing client.
LastNameNo
FirstNameNo
HomePhoneNo
WorkPhoneNo
MiddleNameNo
PostalCodeNo
StateShortNo
UnitNumberNo
DateOfBirthNoUnix timestamp in ms.
MobilePhoneNo
CustomFieldsNoCustom field values (FieldId + Value).
MaritalStatusNo
StreetAddressNo
PractitionerIdNoAssign to this practitioner.
ExternalClientIdNo
AdditionalInformationNo
PrimaryInsuranceCompanyNo
SecondaryInsuranceCompanyNo
PrimaryInsuranceHolderNameNo
PrimaryInsuranceGroupNumberNo
PrimaryInsurancePolicyNumberNo
PrimaryInsuranceRelationshipNo
SecondaryInsuranceHolderNameNo
SecondaryInsuranceGroupNumberNo
SecondaryInsurancePolicyNumberNo
SecondaryInsuranceRelationshipNo
PrimaryInsuranceHolderDateOfBirthNoUnix timestamp in ms.
SecondaryInsuranceHolderDateOfBirthNoUnix timestamp in ms.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare destructiveHint=true, but the description adds high-value context: a create call can silently update an existing client via name/email matching, and sending a partial profile risks unintentionally clearing fields. These are exactly the 'what gets destroyed' facts an agent needs for a mutation tool.

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?

Five sentences, each load-bearing: purpose, branching rule, hidden matching behavior, update workflow, and format conventions. The critical create-vs-update distinction is front-loaded.

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?

For a destructive 37-param upsert with no output schema, the definition covers the essential footguns (dedup matching, field clearing) and format conventions. It could say more about the create path's result or required-field expectations, but nothing critical to calling it safely is missing.

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?

With 37 params at 22% schema coverage, the description cannot fully compensate. It adds important conventions (ClientId behavior, 'field names are IntakeQ's own', Unix-ms dates), but the large majority of fields remain undocumented in both schema and description, so it earns only the baseline.

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?

States a specific verb+resource ('Create a client, or update one') and immediately clarifies the create-vs-update branch via ClientId. It is clearly distinguishable from siblings like intakeq_list_clients, which it references for the update workflow.

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?

Explicitly describes when the tool creates vs updates, discloses the dedup matching fallback (first name + email/phone), and prescribes the correct update workflow (fetch full profile first). This is genuine when/how guidance rather than inference.

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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