Hungarian Financial Regulation MCP

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a distinct purpose: searching regulations, retrieving a specific regulation, listing sourcebooks, searching enforcement actions, checking legal force, and server metadata. No overlap or ambiguity between them.
Naming Consistency5/5
All tools follow a consistent hu_fin_<verb>_<object> pattern (e.g., hu_fin_search_regulations, hu_fin_get_regulation). The only minor exception is hu_fin_about, but it is still recognizable and fits the prefix convention.
Tool Count5/5
Six tools is well-scoped for a financial regulation reference server, covering search, retrieval, listing, enforcement, status checks, and metadata without unnecessary bloat or sparseness.
Completeness4/5
The tool set covers the core lifecycle of querying regulations: discover (search/list), access (get), verify status (check_currency), and enforcement search. A minor gap is the lack of a dedicated get-enforcement-action tool, but the enforcement search likely returns sufficient details for most use cases.
Average 4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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This repository is licensed under Apache 2.0.
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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

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 discloses that the tool returns matching document types, which is useful, but it does not mention default status filtering, result limits, or any safe-read behavior. No contradictions, but richer context would help.
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 sentence with no waste, but it contains a typo ('ajanласок' instead of 'ajanlasok') and a missing accent, which slightly detracts from professionalism. Overall, it is concise and front-loaded.
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?
Given no output schema and no annotations, the description covers the core purpose and document types but omits practical details like default behavior for status, how to filter by sourcebook, or the fact that results may be limited. It is adequate but not comprehensive.
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?
Schema description coverage is 100%, so the baseline is 3. The description adds minimal extra meaning beyond the schema, only implying full-text search semantics. It does not explain defaults (e.g., status defaulting to all) beyond what schema already states.
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 identifies the tool as a full-text search across MNB regulatory provisions, listing specific document types (decrees, recommendations, management circulars). It is distinguishable from sibling tools like hu_fin_search_enforcement and hu_fin_get_regulation.
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 searching regulations but does not explicitly state when to use this tool versus alternatives (e.g., hu_fin_search_enforcement for enforcement actions). No exclusions or alternative recommendations are provided.
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?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It does mention that the tool returns 'status and effective date,' which is useful. However, it does not explicitly state that the operation is read-only or how it behaves if the reference is not found, which is a notable gap for a check-type 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?
The description is exceptionally concise: two short sentences that front-load the purpose and immediately state the return values. There is no redundant or filler content, and every word contributes to understanding the tool's function.
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 low-complexity tool with one parameter and no output schema, the description covers both purpose and return values, which is sufficient for basic invocation. It stops short of explaining the exact format of 'status' or possible error conditions, but those are not critical for a simple read-only check.
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 input schema already provides 100% coverage for the single parameter, including a descriptive example ('MNB rendelet 2/2015'). The tool description only restates that it checks a 'provision reference,' adding little beyond the schema. Baseline 3 is appropriate.
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 specific verb ('Check') and resource ('MNB regulatory provision reference') with a precise scope ('currently in force'). This distinguishes it from sibling tools like hu_fin_search_regulations or hu_fin_get_regulation, which focus on searching or retrieving regulations rather than checking their current force.
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 when one needs to verify whether a specific provision is in force, but it does not explicitly state when to use this tool versus alternatives. No competing tools are mentioned or excluded, leaving the agent to infer the appropriate context from the verb 'Check'.
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?
No annotations are provided, so the description carries the burden. The verb 'get' implies a read-only operation, and the description adds context about acceptable reference formats. However, it does not disclose behavior for not-found cases, output format, or any potential side effects, leaving some ambiguity.
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 consists of two concise sentences, with the primary purpose front-loaded. Every sentence provides useful context without redundancy or unnecessary detail.
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 simple fetch tool with only two parameters and no output schema, the description is mostly complete. It specifies the input format and gives examples. However, it does not clarify what the tool returns (e.g., the full regulation text) or explicitly differentiate it from related search/list tools, which slightly reduces completeness.
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?
Schema coverage is 100%, so both parameters are already well-described. The description's example references ('MNB rendelet 2/2015', 'MNB ajanlas 7/2021') are also present in the schema's parameter description, so no additional meaning is added beyond what the schema 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 the tool's action ('Get') and target resource ('specific MNB regulatory provision'), and specifies the method ('by sourcebook and reference'). This distinguishes it from sibling tools like hu_fin_search_regulations and hu_fin_list_sourcebooks, as it targets a single known provision.
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 retrieving a specific provision when you already have the sourcebook and reference, but it does not explicitly state when to prefer this over search or list tools, nor does it describe alternative scenarios. No clear when/when-not guidance is provided.
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 behavioral disclosure burden. It indicates a search operation, which implies read-only, but does not explicitly mention side effects, return format, or any limitations. It offers some context on content types but lacks richer behavioral detail.
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, front-loaded sentence that efficiently conveys the tool's purpose and scope. Every word adds value, with no redundancy or fluff.
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 search tool with no output schema, the description adequately indicates the type of results (fines, decisions, sanctions). It lacks explicit return-value details, but the purpose is clear enough for an agent to select and invoke the tool correctly.
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?
Schema coverage is 100%, so all three parameters are described in the schema. The description adds no extra meaning beyond the schema, such as query syntax or limit behavior, staying at the baseline of schema-driven clarity.
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: 'Search MNB enforcement actions' with specific categories (fines, decisions, sanctions). It differentiates from siblings like hu_fin_search_regulations by specifying the enforcement focus.
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 use for enforcement-related searches, and sibling names suggest alternatives for regulations. However, it does not explicitly state when to use this tool over others or provide exclusionary guidance.
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?
With no annotations, the description carries the full transparency burden. It clearly indicates a read-only listing operation and specifies the output content (names and descriptions). This is adequate for a simple list tool, though it does not mention potential pagination, ordering, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately states the action and object. Every word adds value, and no extraneous content is present.
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 low complexity (no parameters, no output schema, simple list operation), the description fully covers what an agent needs to know: what it does and what it returns. The mention of 'names and descriptions' clarifies the return value sufficiently.
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?
The tool has zero parameters, so the baseline is 4. The description correctly implies that no input is required, and there is no parameter information needed beyond the schema, which is empty.
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 action ('List'), the resource ('MNB regulatory sourcebooks'), and the scope ('all ... with their names and descriptions'). This distinguishes it from sibling tools like search and get by indicating it returns the full set rather than filtered or individual results.
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 retrieving the complete list of sourcebooks, but it does not explicitly mention when to use this instead of hu_fin_search_regulations or hu_fin_get_regulation. No alternative or exclusionary guidance is provided.
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?
There are no annotations, so the description carries full weight for behavioral disclosure. It explicitly lists the return content (version, data source, tool list) and implies a read-only, safe operation. No contradictions or hidden traits exist.
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 one concise sentence with no unnecessary words. It front-loads the action and resource, then lists the contents, making it efficient and easy to parse.
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?
For a simple metadata endpoint with no output schema, the description fully specifies what the tool returns. Listing version, data source, and tool list gives the agent complete expectation of the response, making the description contextually complete.
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?
The tool has zero parameters, so the description needs to add no parameter semantics. The baseline score of 4 applies, as there is nothing to document and the schema is trivially complete.
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 'Return metadata about this MCP server' with a specific verb and resource, and enumerates what is included (version, data source, tool list). This distinguishes it from sibling tools which focus on regulations, sourcebooks, enforcement, and currency.
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 makes it clear the tool is for server metadata rather than domain queries. While it doesn't explicitly state alternative tools, the purpose is unambiguous and distinct from siblings, so an agent can easily infer when to use this tool.
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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