云启智联 MCP Server
OfficialServer Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each parse tool targets a distinct document type (bank receipt, bank statement, invoice, generic document), and get_task_result is clearly separate for async task management. No overlap.
Naming Consistency4/5Most tools follow parse_* pattern, but get_task_result uses get_ instead. However, the action difference justifies the variation, and naming is otherwise consistent snake_case.
Tool Count5/55 tools is appropriate for a document parsing server, covering major document types and adding a task result retrieval tool without bloat.
Completeness4/5Core document parsing types (receipt, statement, invoice, generic) are covered, and async result retrieval is included. Missing potentially other document types like contracts, but not a significant gap for the stated purpose.
Average 3.2/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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?
No annotations are provided, and the description does not disclose behavioral traits such as authentication requirements, rate limits, or what happens to the file. The api_key parameter hints at auth, but it's not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise but lacks structure. It could benefit from being front-loaded with clearer scoping and parameter explanations.
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?
With 4 parameters, no output schema, and no annotations, the description is incomplete. It fails to explain inputs, outputs, or error handling, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no parameter-level meaning. It does not explain the purpose of api_key, file_path, file_url, or callback_url.
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 states it parses PDF/images to extract structured text, which clearly defines the verb+resource and distinguishes it from specialized siblings like parse_invoice and parse_bank_receipt.
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?
No explicit guidance on when to use this tool vs specialized parsers (parse_invoice, etc.). It is implied for general documents, but not stated.
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 provided. The description lacks details on behavior such as polling requirements, error handling for incomplete tasks, or authentication specifics beyond the api_key parameter.
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?
One concise sentence with no fluff. However, it could be slightly more informative without losing conciseness.
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?
No output schema; description does not mention return format or structure. Lacks context on when to call (after task submission) and prerequisites.
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 description implies task_id identifies the task, but api_key is unclear (likely authentication). With 0% schema coverage, only partial semantics are conveyed.
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 verb 'query' and the resource 'result of asynchronous parsing task'. It effectively differentiates from sibling parse tools that initiate tasks.
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 (e.g., after task submission) or not to use it (e.g., before completion). No alternatives mentioned.
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 fails to disclose behavioral traits such as whether the operation is read-only, if it requires network access or authentication beyond the api_key, or any potential side effects. It only says 'parse' and returns data, lacking detail on process limitations.
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 immediately states the verb and resource. It is efficient but could be more structured by separating input requirements from output details.
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 4 parameters, no output schema, and no annotations, the description is incomplete. It does not explain the required combination of file_path or file_url, nor the asynchronous nature possibly implied by callback_url, nor what the return format looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description does not explain any of the 4 parameters (api_key, file_path, file_url, callback_url). It only mentions the overall purpose, leaving parameter roles ambiguous.
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 verb 'parse', the resource 'VAT invoice images or PDF', and lists specific return fields (invoice code, number, date, amount, buyer/seller info). It distinguishes from sibling tools that parse bank receipts, bank statements, or generic documents.
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 for invoices but does not explicitly state when to use this tool versus alternatives like parse_bank_receipt. No guidance on prerequisites or when not to use.
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, leaving the description to fully convey behavioral traits. It mentions returning structured data but omits critical details such as file format support, required permissions, error handling, or any side effects of the operation.
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 that front-loads the primary action and output. No unnecessary words; every part contributes to understanding the tool's main purpose.
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 has 4 parameters, no output schema, and no annotations, the description is too sparse. It lacks information on required input formats, parameter interdependencies, return value structure, and potential limitations, leaving significant gaps for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 4 parameters with 0% description coverage. The description adds context by mentioning image or PDF inputs, but fails to explain the specific role of each parameter (api_key, file_path, file_url, callback_url) or the constraints on their usage.
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 parses bank statement images or PDFs and returns structured data like account info and transactions. It is specific to bank statements, distinguishing it from siblings like parse_bank_receipt or parse_invoice.
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 bank statement parsing, providing some context for when to use it. However, it offers no explicit guidance on when not to use it or how it compares to alternatives like parse_document or parse_bank_receipt.
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. It discloses the auto-cropping feature and the structured return fields but lacks details on error handling, authentication beyond api_key, or limitations like file size or supported image formats.
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 with two sentences: one explaining the core functionality and the second listing output fields. It is front-loaded but could be slightly more structured (e.g., separated sections for process and output).
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 4 parameters, no output schema, and no annotations, the description covers the main purpose and return fields but lacks details on async behavior (callback_url), file format limits, timeouts, or integration with get_task_result. Adequate but incomplete.
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%, so baseline is 3. The description adds no additional nuance beyond the schema; it merely restates that callback_url is optional and the api_key is required. No parameter-level elaboration is provided.
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 parses bank receipt images/PDFs, with automatic cropping of multiple receipts per page, and lists the structured fields returned. It distinguishes from siblings like parse_bank_statement and parse_invoice.
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 for bank receipt parsing but does not explicitly state when to use it versus alternatives like parse_bank_statement or parse_document. No exclusions or prerequisites are mentioned.
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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