mcp-logistics-tracker
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: listing carriers, fetching current status, and retrieving full history. There is no overlap or ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun snake_case pattern (get_tracking_history, list_carriers, track_shipment), making them predictable and readable.
Tool Count5/5With 3 tools covering listing carriers, current status, and history, the number is well-scoped for a basic logistics tracking server. Each tool earns its place.
Completeness4/5The tool surface covers the core tracking workflow (carrier discovery, current status, full history). While additional features like batch tracking or validation could be useful, there are no critical gaps.
Average 3.9/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 transparency burden. It discloses chronological ordering and automatic removal of hyphens/spaces from tracking numbers. However, it does not mention error handling, rate limits, or read-only behavior.
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 concise: two sentences for purpose, then a clear Args section. No unnecessary words, front-loaded with main functionality.
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?
Output schema exists, so return values are covered. However, the description lacks references to sibling tools (e.g., 'list_carriers' for valid codes) and does not provide broader context like authentication or when to prefer this tool over 'track_shipment'.
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?
Schema coverage is 0%, so the description compensates well: it provides carrier examples (yamato, sagawa, japanpost) and explains tracking number formatting (numbers, hyphens/spaces removed). This adds significant value beyond the schema's empty type strings.
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 it returns delivery event history for a given carrier and tracking number in chronological order. The verb '返す' (returns) and specific resource '配送イベント履歴' are present, distinguishing it from siblings like 'track_shipment' which may provide a different scope.
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 explicit guidance on when to use this tool vs alternatives like 'track_shipment' or 'list_carriers'. There is no mention of prerequisites or when not to use it.
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 provided, so description carries full burden. It mentions that tracking_number hyphens/spaces are auto-removed, a helpful behavioral detail. However, it does not disclose authentication needs, rate limits, or error handling for invalid inputs.
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?
Description is concise with two sentences: first defines purpose, second details arguments. No wasted words. Could be slightly more structured (e.g., bullet points) but remains efficient.
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?
Given that an output schema exists, description need not explain return values. It covers purpose, arg details, and a behavioral note. For a simple lookup tool with 2 required params, this is adequately 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?
Schema description coverage is 0%, so description adds meaning. For 'carrier', it lists example values (yamato, sagawa, japanpost). For 'tracking_number', it explains it must be digits and auto-removes hyphens/spaces, which is not evident from the schema.
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?
Description clearly states verb '返す' (return) and resource '現在の配送状況' (current delivery status). It distinguishes from siblings 'get_tracking_history' and 'list_carriers' by implying it returns the latest status rather than history or carrier list.
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?
Description indicates when to use (to get current status for a carrier and tracking number) but does not explicitly state when not to use or provide alternatives. Sibling names imply other tools but are not mentioned.
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 full burden. It clearly states the tool returns a list of carriers, which is adequate for a simple read-only operation. No hidden behaviors are expected.
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 concise sentence in Japanese, front-loaded with the action and listing the carriers. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with an output schema, the description is fully complete—it states what the tool returns. No additional context is necessary.
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 does not need to add parameter information.
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 it returns a list of supported carriers and names them (Yamato Transport, Sagawa Express, Japan Post). This is a specific verb+resource with clear scope.
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 guidance on when to use this tool vs siblings like get_tracking_history or track_shipment. The usage context is only implied through naming.
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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