Discover Swedish MSK clinics on fysio.care: search clinics, services, and open appointment times.
Scored across 4 tools
Each tool has a clearly distinct purpose: searching clinics, listing services, getting available slots, and finding the next available date. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (e.g., search_clinics, list_clinic_services, get_available_slots). No mixing of conventions.
With 4 tools, the server is well-scoped for clinic discovery and appointment slot checking. No unnecessary clutter or missing essentials.
The tool set fully covers the discovery workflow: find clinics, see their services, check availability, and handle empty slots with next available date. The server explicitly excludes booking, so no gap.
Free appointment slots for one bookable service variant at one clinic, up to 14 days ahead. Each slot carries a FHIR Slot resource and a bookingUrl where the PATIENT completes the booking themselves on the web (this server never books).
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Window length in days. | |
| from_date | No | Window start (YYYY-MM-DD, clinic runs Europe/Stockholm). Defaults to today. | |
| clinic_slug | Yes | The clinic slug from search_clinics (the URL segment, e.g. "mickes-klinik-lund"). | |
| service_variant_id | Yes | A bookable service variant id from list_clinic_services. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds context about the FHIR Slot resource and bookingUrl, and clarifies that the server never books. This provides useful behavioral detail beyond annotations, but no further depth on authentication or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first covers purpose and scope, the second adds key behavioral detail. Every sentence provides value with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the lack of output schema, and annotations covering safety, the description is complete. It explains what is returned (slots with FHIR resource and bookingUrl) and the booking behavior, which is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with all four parameters well-described in the input schema. The description adds only the phrase 'up to 14 days ahead', which aligns with the days parameter. It does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves free appointment slots for one specific service variant at one clinic, within a 14-day window. It uses specific verbs and resources, and distinguishes itself from sibling tools that handle dates, services, or clinics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when slots for a specific service and clinic are needed, and mentions the booking flow. However, it does not explicitly state when not to use or directly name alternative tools, though the differentiation is clear from the sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Earliest free slot for a service variant, scanning up to 90 days ahead. Use when get_available_slots comes back empty.
| Name | Required | Description | Default |
|---|---|---|---|
| clinic_slug | Yes | The clinic slug from search_clinics (the URL segment, e.g. "mickes-klinik-lund"). | |
| service_variant_id | Yes | A bookable service variant id from list_clinic_services. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true. Description adds behavioral detail about scanning up to 90 days ahead, which is not in annotations. No contradictions, but could mention return format or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Purpose is front-loaded in the first sentence, making it immediately clear what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two well-documented parameters and no output schema, the description is fairly complete. It covers purpose, usage scenario, and a key behavioral constraint (90-day scan). Could mention return value format, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and both parameters have descriptions in the schema. The tool description does not add any additional meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it finds the earliest free slot for a service variant, scanning up to 90 days ahead. It distinguishes itself from sibling tool 'get_available_slots' by explicitly stating when to use it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use when get_available_slots comes back empty,' providing clear, actionable guidance on when this tool is appropriate instead of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the bookable services of one clinic, with duration, price (SEK) and a FHIR HealthcareService per bookable variant. The variant id is what get_available_slots takes.
| Name | Required | Description | Default |
|---|---|---|---|
| clinic_slug | Yes | The clinic slug from search_clinics (the URL segment, e.g. "mickes-klinik-lund"). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as read-only. The description adds transparency by detailing the output fields (duration, price, HealthcareService, variant id). No behavioral contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core action and key output details. Every word serves a purpose with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains the return type (duration, price, HealthcareService, variant id) and connects to sibling tools. It lacks details like ordering or pagination, but for a simple list tool it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter clinic_slug is well-described in the input schema itself (explaining it's the URL segment from search_clinics). The description does not add additional meaning beyond what the schema provides, so baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists bookable services for a clinic, including duration, price, and variant id. It distinguishes itself from siblings by mentioning the variant id is used by get_available_slots, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing services before calling get_available_slots, but no explicit when-to-use or when-not-to-use guidance is given. It somewhat relies on sibling context for differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the public directory of Swedish MSK clinics (fysioterapi, naprapati, kiropraktik m.fl.) on fysio.care. Returns published clinics with FHIR Organization resources. Use list_clinic_services next to see what a clinic offers.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | Exact city name, e.g. "Lund". | |
| limit | No | ||
| query | No | Case-insensitive clinic-name substring. | |
| modality | No | Only clinics offering this treatment modality. | |
| friskvard | No | Only clinics where friskvårdsbidrag can actually be spent. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description reinforces that the tool searches a public directory, which is consistent. The description adds minimal behavioral context beyond the annotation (e.g., no mention of rate limits, data freshness, or authentication requirements).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded paragraph with three sentences. Every sentence adds value: purpose, what it returns, and a workflow hint. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description mentions the output format ('FHIR Organization resources'), but without an output schema, this is vague. It does not describe pagination, result limits, or how to interpret the results. The suggestion to use list_clinic_services next partly compensates, but the return structure remains under-specified for a tool with 5 parameters and no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 80% (4 of 5 parameters have descriptions). The description does not add new information about parameters beyond what is already in the schema. It repeats the concept of 'clinic-name' but does not clarify constraints like the enumeration for modality or the meaning of friskvard.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action (Search), the resource (public directory of Swedish MSK clinics on fysio.care), and the output format (FHIR Organization resources). It also distinguishes the tool from the sibling list_clinic_services by suggesting it as a next step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear follow-up action ('Use list_clinic_services next to see what a clinic offers'), indicating a workflow. However, it does not explicitly state when to use this tool versus other siblings like get_available_slots or get_next_available_date, leaving the comparison implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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