rijschool-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools target clearly distinct resources: nearby search, text search, detail lookup, price statistics, and city/province aggregates. The only mild overlap is between rijscholen_in_de_buurt and zoek_rijscholen, but their descriptions make the coordinate-vs-filter distinction clear.
Naming Consistency3/5
All names use lowercase snake_case and are readable Dutch, but the style is mixed: zoek_rijscholen is verb-first while the rest are noun phrases or descriptive labels like rijscholen_in_de_buurt. There is no uniform verb_noun or resource_noun convention.
Tool Count5/5
Six tools form a well-scoped set for a driving-school directory: search, nearby lookup, detail retrieval, and three aggregate/statistical views. Each tool has a clear purpose and the count is appropriate for the domain.
Completeness5/5
The surface covers the full read-only workflow: finding schools by text or location, retrieving full details, and getting price/statistical overviews at national, city, and province levels. There are no obvious missing operations for the apparent purpose of the server.
Average 3.8/5 across 6 of 6 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden of disclosing side effects or read-only behavior. It implies a read operation by saying 'gegevens' but does not explicitly state that no modifications occur, nor does it mention error behavior or data availability guarantees.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, reasonably concise sentence that lists the data fields. It front-loads the main purpose ('Alle gegevens van één rijschool') and avoids unnecessary fluff, though the long enumeration makes it slightly dense.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not clarify parameter combinations or whether at least one parameter is required, especially since all parameters are optional in the schema. There is no output schema and no indication of return format, leaving ambiguity about how to invoke the tool correctly.
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?
All three parameters have descriptions in the schema, and the schema coverage is 100%. The parameter descriptions add useful context, such as using 'naam' when the ID is unknown and using 'stad' to disambiguate common names, going beyond simple field labels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns 'alle gegevens' (all data) of a single driving school and enumerates the specific data fields. It distinguishes from siblings by emphasizing 'één rijschool' (one driving school), though it does not explicitly name alternative tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the sibling tools such as 'zoek_rijscholen' or 'rijschool_in_de_buurt'. It does not mention any selection criteria, prerequisites, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the return content (cities with number of schools, average pass rate, price) and the default behavior when no province is specified (all of the Netherlands). However, it does not mention pagination, sorting, or error handling, which are potential gaps given the lack of annotations.
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 a single, concise sentence efficiently conveying the tool's purpose and key default behavior without unnecessary detail. It is well-structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description provides the core information about the returned data, it lacks details on output format (e.g., list of city names with fields) and does not mention any additional limits or ordering. Given the absence of an output schema, these details are missing but may not be critical for this simple tool.
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?
All three parameters are described with clear semantics: limiet (default 50), provincie (restricts to one, with allowed values listed), and minimum_rijscholen (default 3). The schema coverage is 100%, and the descriptions add valuable default values and constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns all places with driving schools, including counts, average pass rate, and average price. It is specific to listing cities with aggregates, and the mention of province filtering helps distinguish it from sibling tools focused on individual schools or provinces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It only hints at optional province filtering but does not explain scenarios where this tool is preferred over siblings like 'zoek_rijscholen' or 'rijschool_in_de_buurt'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states what data is returned (the twelve provinces with listed attributes) but does not disclose potential limitations, error conditions, or whether the output is a fixed list. It is transparent about the content but lacks details on behavior in edge cases.
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 a single, concise sentence that immediately states the subject (the twelve provinces) and the key associated data. No unnecessary words or repetition.
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 provides enough context for an agent to understand the tool's purpose and the data it returns, even without an output schema. It specifies the exact attributes included for each province, though it omits details about the exact format or data types.
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?
There are no parameters, and the schema description coverage is effectively 100%. The baseline for parameter semantics is therefore 3, and the description adds no additional parameter-related information because none exists.
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 provides the twelve provinces with specific accompanying data (number of driving schools, average pass rate, average price per lesson, largest cities). It is specific and distinguishes itself from sibling tools that focus on individual driving schools, prices, or cities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives. It does not mention any conditions or typical use cases, leaving the agent to infer applicability solely from the purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the data source (driving school websites) and notes prices are indicative. It does not mention any side effects or explicitly state that the tool is read-only, but given the absence of annotations, the description is reasonably transparent about the expected behavior of returning price statistics.
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 a single, concise sentence that conveys all essential information without redundancy or unnecessary detail. It is well-structured and easy to parse.
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 the core output (cheapest, median, most expensive) and the geographic scope options. It does not specify the exact return format or the behavior when both parameters are used, but for a simple price-statistics tool, this is largely sufficient. Minor gaps prevent a perfect score.
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?
The description adds that parameters limit scope to a single city or province, and that omitting both yields national results. However, it does not elaborate on the interaction when both 'stad' and 'provincie' are provided, leaving ambiguity about whether they combine or one takes precedence.
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's purpose: providing the price distribution (cheapest, median, most expensive) for driving lessons, with scope options (national, city, or province). It explicitly distinguishes this from sibling tools that locate driving schools or list cities/provinces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for price statistics (e.g., when you need cost comparisons) but does not explicitly state when to use this tool over alternatives like 'zoek_rijscholen' or 'rijschool'. It lacks direct guidance on choosing between national vs. local scopes or clarifying the effect of combining both parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It states the output includes distance and the purpose, but it does not explicitly mention that it is a read-only operation, potential error conditions, or what happens if no results are found. This is acceptable but not fully transparent.
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 concise, consisting of two clear sentences. The first sentence states the function, and the second provides a usage hint. No unnecessary words 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 simplicity and the presence of sibling tools, the description is sufficient. It covers the core purpose, the type of output, and a relevant usage scenario. The absence of an output schema is not a problem as the description hints at the output structure (distance).
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?
The schema already provides 100% coverage of parameter descriptions, so the baseline is 3. The description adds some context about coordinates and municipal boundaries, but it does not significantly enhance understanding of parameters like 'straal_km' or 'minimum_examens' beyond what the schema already provides.
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 that the tool finds the nearest driving schools to a point and includes the straight-line distance. It also differentiates the tool from potential siblings by mentioning use with coordinates and when municipal boundaries are not the relevant scope.
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 gives usage conditions: use when you have coordinates and no place name, or when the municipal boundary isn't the relevant boundary. This provides clear guidance on when to select this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behaviors such as typo tolerance ('verdraagt een typefout'), dynamic default sorting, and the fact that it returns a brief overview. Since no annotations are provided, the description carries the burden, and it does so adequately, though it does not mention pagination or result size limits beyond the 'limiet' parameter.
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 concise, consisting of one well-structured sentence and a brief note about usage. It conveys the core functionality and important nuances without redundancy, making it easy to parse quickly.
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 absence of an output schema, the description provides sufficient context by stating it returns a brief overview, which implies a list of results. It does not specify exact output fields, but that omission is acceptable for a search tool when a sibling tool provides detailed information for a single school.
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?
All parameters have schema descriptions, but the tool description adds meaningful semantics beyond the schema: e.g., 'zoekterm' explains typo tolerance, 'sorteer' explains default behavior, and 'minimum_examens' explains the implicit default. This helps the agent use parameters effectively.
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's function: searching driving schools using free text, city, province, or service area, with various filters. It distinguishes itself from siblings by explicitly noting that 'rijschool' should be used for full details of a single school, and the general search nature contrasts with 'rijscholen_in_de_buurt'.
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 provides explicit guidance on when to use this tool versus the sibling 'rijschool' tool, and it explains the behavior of key filters (e.g., sorting defaults, minimum examens default). This helps an agent choose the right tool and use filters correctly.
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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