Finance MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct financial asset or data type (exchange rate, bitcoin, gold, S&P 500). The get_all_prices tool is clearly a bulk variant, but its purpose is distinct from individual getters, and descriptions make the choice unambiguous.
Naming Consistency5/5All tools follow a consistent get_ prefix with a noun describing the data (exchange_rate, bitcoin_price, gold_price, sp500, all_prices). This is a uniform and predictable pattern.
Tool Count5/5With only 5 tools, the server is well-scoped for a financial data retrieval service. Each tool serves a specific purpose, and there is no unnecessary bloat or sparse implementation.
Completeness4/5The server covers the four core assets it mentions (exchange rates, bitcoin, gold, S&P 500) and adds a bulk fetch. Minor gaps exist, such as no support for additional currency pairs or historical data, but these are not critical for the stated real-time focus.
Average 3.7/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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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?
With no annotations, the description must disclose behavioral traits on its own. It only mentions 'real-time' and the supported pairs, omitting the return format, rate type, or any limitations such as delayed data or API restrictions, leaving the behavior under-specified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly conveys the purpose and supported pairs, with no filler or repetition. It is well-structured and front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple tool with one parameter, but the absence of an output schema means the description should explain what data is returned. It does not, and it also lacks any mention of the response format or the source of the rates, making the description incomplete for robust agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single 'pair' parameter is fully described in the schema with an enum and description, and the description simply repeats the allowed values without adding semantics. Since schema coverage is 100%, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool 'fetches real-time exchange rate information' (실시간 환율 정보를 가져옵니다) and names the specific currency pairs (USD/KRW, JPY/KRW). This clearly defines the verb+resource+scope, distinguishing it from sibling tools that fetch other asset prices.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for exchange rate lookups but does not provide explicit when-to-use or when-not-to-use guidance, nor does it reference alternative tools for other asset types. An agent must infer usage from the tool name and domain rather than from direct instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
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 price is real-time and based on 3.75 grams, but does not describe return format, caching, or any error/rate-limit behavior. This is minimal for a tool with no annotation context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence that immediately states the tool's core function and the unit. Every word earns its place; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read tool, the description is adequate but leaves gaps: no return format, no mention of the currency (likely KRW but unstated), and no guidance on how this relates to other tools. The lack of output schema makes this slightly under-specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so baseline is 4. The description adds useful context about the measurement basis (3.75g), which helps the agent interpret the output even though no parameters are involved.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb '가져옵니다' (retrieve) and a specific resource '실시간 금 시세' (real-time gold price), with a clarifying unit (3.75g). This distinguishes it from sibling tools like get_exchange_rate and get_bitcoin_price.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No mention of when to use this tool versus alternatives like get_all_prices. The description provides no exclusions or preferences, so the agent must infer usage solely from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action (fetching the index) and provides no detail about data source, update frequency, return format, or any caveats. The lack of any behavioral context beyond the purpose itself is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly states the purpose without any filler. Every word earns its place, and the structure is appropriately front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool, this is minimally viable. The purpose is clear and invocation is straightforward. However, the lack of any return value description (no output schema exists) and the absence of usage guidance relative to sibling tools leave clear gaps in the overall context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is empty. Per the guidelines, the baseline for 0 params is 4. The description adds no parameter information, but none is needed since there are no arguments to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('가져옵니다' / gets) and a specific resource ('S&P 500 지수' / S&P 500 index). This distinguishes it from sibling tools like get_exchange_rate or get_bitcoin_price, each targeting a different financial data point.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as get_all_prices. The description does not mention any context, exclusions, or comparisons to sibling tools, leaving the agent without decision support for selection.
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 full burden of behavioral disclosure. It states that all financial info is returned but does not describe the response structure, timing, or any potential limitations. For a simple read-only aggregation, this is moderately transparent but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, concise sentence that is front-loaded with the primary action and includes parenthetical detail for the exact data types. Every word earns its place, with no unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters, no output schema, and no annotations, the description provides sufficient context: it names the specific financial instruments covered. While it doesn't describe return format or usage scenarios, the simplicity of the tool means this is mostly complete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema is trivially complete. The description does not need to add parameter semantics, and with no parameters, the baseline of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that this tool fetches all financial information at once, explicitly listing the components (exchange rate, bitcoin, gold, S&P500). This distinguishes it from sibling tools that fetch individual data points, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that this tool is for getting multiple financial data points simultaneously, but it does not explicitly contrast with sibling tools or state when to prefer this over individual getters. There is no explicit alternative naming or exclusion, so the guidance remains implicit rather than explicit.
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. It adds 'real-time' and 'KRW' context, but does not disclose return format, failure behavior, or other operational details. The added context is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. Every part contributes to meaning, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zero-parameter tool with no output schema, the description is adequate: it states the purpose and currency. It lacks details like return format, but given the simplicity, it is sufficiently complete for an AI agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the baseline is 4. The description adds no parameter-specific details, but none are needed. The tool is self-contained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action (fetch real-time price) and resource (Bitcoin price in KRW), distinguishing it from siblings like gold or exchange rates. The verb and object are explicit and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for real-time Bitcoin price in KRW, providing clear context. It does not explicitly mention alternatives or exclusions, but the intended use is evident given the sibling tools.
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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