Toofi Dental Planning MCP

List demo patients

list_demo_patients

Read-onlyIdempotent

List public no-PHI Toofi demo patients so agents can inspect patient response structure.

Input Schema

TableJSON Schema

Name	Required	Description
`agent_id`	No	Calling agent identifier.
`clinic_id`	No	Clinic identifier for mandate-scoped production execution.
`intent_id`	No	Root agent intent id.
`mandate_id`	No	Clinic or agent mandate id. Optional in public demo mode.
`request_id`	No	Idempotency and correlation id echoed in Toofi responses.
`principal_id`	No	Human or clinic principal on whose behalf the agent acts.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`ok`	No
`mode`	No
`status`	No
`endpoint`	No
`timestamp`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedMay 11, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds that patients are 'public no-PHI', which is useful data-sensitivity context but not a rich behavioral trait like auth requirements or side effects. With annotations covering safety, a score of 3 is appropriate.

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?

A single, front-loaded sentence of 12 words that clearly states the action and purpose. Every word earns its place with no redundancy or filler.

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?

Given the simple list operation, the presence of an output schema, and comprehensive annotations, the description is nearly complete. It explains the tool's purpose and data type (demo, no-PHI). A minor gap is not explicitly mentioning the distinction from production tools like list_patients, but the 'demo' label makes it sufficiently clear.

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?

All 6 parameters have full descriptions in the schema (100% coverage), so the description does not need to repeat parameter info. The description adds no parameter-level meaning, which aligns with the baseline of 3 for high schema coverage.

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 uses a specific verb ('List') and clearly identifies the resource ('public no-PHI Toofi demo patients') with a stated purpose ('so agents can inspect patient response structure'). This distinguishes it from siblings like list_patients and get_demo_patient.

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 implies usage for demo/inspection scenarios and explicitly notes that data is public and contains no PHI, which differentiates it from production tools. However, it does not explicitly name alternatives or state when not to use it, though the 'demo' label provides clear context.

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

B3.3/5.0

Disambiguation3/5

Several tools have overlapping purposes, particularly example_en, example_pl, example_ru, example_sk, example_ua, example_uk, and get_example_result, which all return example PDFs. Also, example_ua and example_uk are explicitly aliases for the same Ukrainian example, creating direct ambiguity. Core clinical tools are distinct, but the example/demo cluster muddies the boundary.

Naming Consistency4/5

Most tools follow a snake_case verb_noun pattern (e.g., list_patients, create_agent_checkout_session, generate_price_estimate), but a few deviations exist: example_en/pl/ru/sk/ua/uk lack a verb prefix, and get_example_result seems to duplicate example_en. The 'pano' abbreviation in start_pano_markup is also slightly inconsistent. Overall, the pattern is mostly predictable.

Tool Count2/5

With 32 tools, the count is too high for the apparent scope of dental planning. Many tools are redundant example/demo variants (e.g., 6 language-specific example tools plus get_example_result, and multiple demo getters/listers). This bloat suggests the tool set could be consolidated to a more focused 15-20 tools without losing core functionality.

Completeness3/5

The core workflow is covered: generating plans, retrieving patients/plans, pricing, and billing. However, there are notable gaps such as no update or delete operations for plans or patients, no create patient tool, and no way to modify pricing beyond import_price_csv. The demo tools partially compensate by offering sample data, but the production lifecycle is incomplete.

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