MCP Stock Assistant
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: get-market-index focuses on market indices, get-stock-history retrieves historical data for individual stocks, and get-stock-info provides real-time information for individual stocks. There is no overlap in functionality, making it easy for an agent to select the appropriate tool.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with hyphens (e.g., get-market-index, get-stock-history, get-stock-info). The naming is uniform and predictable, using the same verb 'get' followed by a descriptive noun phrase.
Tool Count3/5With only 3 tools, the server feels thin for a stock assistant domain. While the tools cover basic data retrieval (indices, historical data, real-time info), it lacks operations for analysis, trading, or portfolio management, which are common in stock-related tools. The count is borderline but reasonable for a minimal setup.
Completeness2/5The tool surface is significantly incomplete for a stock assistant. It only provides read-only data retrieval (get operations) with no ability to create, update, or delete (e.g., no tools for setting alerts, managing watchlists, or executing trades). This will cause agent failures when trying to perform common stock-related tasks beyond basic queries.
Average 3.1/5 across 3 of 3 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
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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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions data retrieval ('获取') and supports different K-line periods, but fails to disclose critical traits such as rate limits, authentication requirements, data freshness, error handling, or response format. For a data-fetching tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
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 concise and front-loaded, stating the core purpose in the first clause. It uses two sentences efficiently: one for the main action and another for usage context. There's no wasted text, and it avoids redundancy, though it could be slightly more structured for clarity.
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?
Given the tool's complexity (3 parameters, no output schema, no annotations), the description is incomplete. It covers the basic purpose and implied usage but lacks details on behavioral aspects (e.g., rate limits, auth), response format, and explicit sibling differentiation. Without annotations or output schema, more context is needed for effective agent use, making it inadequate for a data retrieval tool.
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?
Schema description coverage is 100%, with all parameters well-documented in the schema itself (e.g., 'stock_code' as stock code/name, 'period' as time cycle with enum values, 'days' as number of days). The description adds minimal value beyond the schema, only reiterating support for daily, weekly, and monthly K-lines without providing additional syntax or usage details. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '获取单个股票的历史数据、过去价格、K线数据' (get historical data, past prices, K-line data for a single stock). It specifies the resource (stock) and actions (retrieve historical data), distinguishing it from siblings like 'get-market-index' and 'get-stock-info' by focusing on historical price data rather than market indices or general stock information. However, it doesn't explicitly contrast with siblings in the text, keeping it from a perfect score.
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 usage context with '用于分析股票过去的表现' (used for analyzing past stock performance), suggesting when to use this tool. However, it lacks explicit guidance on when to choose this over alternatives like 'get-stock-info' (which might provide current data) or 'get-market-index', and doesn't mention any prerequisites or exclusions. The guidance is present but not comprehensive.
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 states the tool provides '实时当前信息' (real-time current information), which implies it's a read-only operation with fresh data, but it doesn't disclose critical traits like rate limits, authentication needs, data freshness guarantees, error handling, or whether it's a safe operation. For a tool with zero annotation coverage, this leaves significant gaps in behavioral understanding.
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, efficient sentence that front-loads the core purpose ('获取单个股票的实时当前信息') and lists key data points without unnecessary elaboration. Every word earns its place, making it highly concise and well-structured for quick comprehension.
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?
Given the tool's low complexity (one parameter, no nested objects) and lack of annotations or output schema, the description is minimally adequate. It covers the basic purpose and data scope, but it doesn't address behavioral aspects (e.g., safety, performance) or provide usage guidance relative to siblings. For a simple read tool, this is borderline viable, but it could be more complete by adding context on limitations or alternatives.
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 schema description coverage is 100% (the single parameter 'stock_code' is fully documented in the schema with a clear description and examples). The description adds no additional meaning about parameters beyond what the schema provides—it doesn't explain parameter semantics, constraints, or usage nuances. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '获取单个股票的实时当前信息' (get real-time current information for a single stock). It specifies the verb (获取/get) and resource (股票/stock), and lists key data points like price, change percentage, and volume. However, it doesn't explicitly distinguish this tool from its sibling 'get-stock-history' (which likely provides historical data), so it doesn't fully achieve sibling differentiation.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools 'get-market-index' (for market indices) or 'get-stock-history' (for historical data), nor does it specify any prerequisites, exclusions, or contextual cues for selection. Usage is implied by the description's focus on '实时当前信息' (real-time current information), but this is insufficient for explicit guidance.
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 full burden. The description mentions '实时数据' (real-time data), which is useful behavioral context about freshness. However, it doesn't disclose other important traits: whether this is a read-only operation, authentication requirements, rate limits, error conditions, or what format the data returns. For a data retrieval tool with zero annotation coverage, this is insufficient.
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, efficient Chinese sentence that states exactly what the tool does. Every word earns its place: it specifies the action (获取 - get), the resource (大盘指数概览信息 - market index overview information), and the scope (上证指数和深证成指等主要指数的实时数据 - real-time data for Shanghai Composite, Shenzhen Component and other major indices). No wasted words.
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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is reasonably complete for a basic data retrieval tool. It tells what data is returned and that it's real-time. However, without annotations or output schema, it should ideally mention more about the return format, data fields, or authentication requirements to be fully complete.
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 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters since none exist. It does mention the scope ('大盘指数概览信息' - market index overview information) which helps understand what data will be returned, adding value beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '获取大盘指数概览信息' (get market index overview information) with specific resources mentioned ('上证指数和深证成指等主要指数' - Shanghai Composite Index, Shenzhen Component Index, and other major indices). It distinguishes from sibling tools (get-stock-history, get-stock-info) by focusing on market indices rather than individual stocks. However, it doesn't explicitly contrast with siblings in the description text.
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?
The description provides no guidance on when to use this tool versus alternatives. While it's clear this tool is for market indices rather than individual stocks (implied differentiation from siblings), there's no explicit 'when-to-use' or 'when-not-to-use' guidance, nor any mention of prerequisites or context for usage.
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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