Qinglong MCP Server

by pholex

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no ambiguity. Tools target specific resources (tasks, subscriptions) and actions (get logs, get status, list, run), ensuring agents can easily differentiate between them.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., get_task_logs, list_qinglong_tasks, run_subscription). The naming is uniform and predictable, making the set easy to navigate.
Tool Count5/5
With 7 tools, the server is well-scoped for managing Qinglong tasks and subscriptions. Each tool serves a clear function, covering core operations without being overly sparse or bloated.
Completeness4/5
The tool set provides strong coverage for task and subscription management, including listing, running, and monitoring. A minor gap exists in update or delete operations for tasks and subscriptions, but agents can still handle most workflows effectively.
Average 3/5 across 7 of 7 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
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This repository is licensed under Apache 2.0.
This repository includes a README.md file.
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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 full burden for behavioral disclosure. It states the action ('run') but doesn't clarify if this is a read-only operation, a mutation, whether it's destructive, what permissions are needed, or what happens upon execution (e.g., triggers tasks, sends notifications). This is a significant gap for a tool with no annotation coverage.
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, efficient sentence with zero wasted words. It's appropriately sized and front-loaded, directly stating the tool's action without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by 'run' (likely a mutation), no annotations, no output schema, and sibling tools suggesting task-related operations, the description is incomplete. It doesn't explain what 'running a subscription' does, what the expected outcome is, or how it differs from similar tools, leaving critical gaps for agent understanding.
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%, with the parameter 'subscription_id' documented as '订阅 ID' (subscription ID). The description adds no additional meaning beyond this, such as how to obtain valid IDs or format requirements. With high schema coverage, the 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '运行指定的订阅' (run the specified subscription) states a verb+resource combination, but it's vague about what 'running a subscription' actually entails. It doesn't distinguish this tool from sibling tools like 'run_task' or 'run_task_async', leaving ambiguity about whether this executes tasks, triggers workflows, or performs another action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. The description doesn't mention prerequisites (e.g., needing a valid subscription_id from 'list_subscriptions'), exclusions, or comparisons to siblings like 'run_task' or 'run_task_async'. This leaves the agent without context for tool selection.
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 it 'gets' logs, implying a read-only operation, but doesn't specify if it retrieves all logs, recent logs, or paginated results. It also doesn't mention authentication needs, rate limits, or error conditions (e.g., invalid task ID). The description adds minimal context beyond the basic action.
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, efficient sentence in Chinese that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse. Every part of the sentence earns its place by specifying the system (Qinglong panel), target (specified tasks), and what is retrieved (execution logs).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a read operation with no output schema and no annotations), the description is incomplete. It doesn't explain what the logs contain (e.g., timestamps, output, errors), how they are returned (e.g., text, JSON), or if there are limitations (e.g., log size, retention). For a tool that likely returns detailed data, more context is needed to help the agent use it effectively.
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 has 100% description coverage, with 'task_id' documented as '任务 ID' (task ID). The description adds no additional meaning beyond this, such as format examples (e.g., numeric ID from 'list_qinglong_tasks') or constraints (e.g., must be an existing task). With high schema coverage, the baseline is 3, as the schema does the heavy lifting without description enhancement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('获取' meaning 'get') and resource ('青龙面板中指定任务的执行日志' meaning 'execution logs of specified tasks in Qinglong panel'). It distinguishes from siblings like 'get_task_status' (status vs logs) and 'list_qinglong_tasks' (list tasks vs get logs). However, it doesn't explicitly mention it's for historical logs versus real-time monitoring, which could further differentiate from 'run_task' tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 prerequisites (e.g., needing a valid task ID from 'list_qinglong_tasks'), exclusions (e.g., not for real-time logs during execution), or comparisons to siblings like 'get_task_status' for status information instead of logs. Usage is implied by the name but not explicitly 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action ('get status') but doesn't disclose traits like whether it's read-only, requires authentication, has rate limits, or what the response format might be. This is inadequate for a tool with zero annotation coverage.
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, efficient sentence in Chinese that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'execution status' entails (e.g., pending, running, success, failure), return values, or error handling, leaving significant gaps for a tool that interacts with task management.
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 schema description coverage is 100%, with the single parameter 'task_id' documented as '任务 ID' (task ID). The description adds no additional meaning beyond this, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('获取' meaning 'get') and resource ('青龙面板中指定任务的执行状态' meaning 'execution status of specified task in Qinglong panel'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_task_logs' or 'list_qinglong_tasks', which might also involve task information retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 prerequisites, when-not scenarios, or comparisons to siblings like 'get_task_logs' (for logs) or 'list_qinglong_tasks' (for listing tasks), leaving usage context implied at best.
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 provided, the description carries full burden. It discloses the asynchronous nature ('不等待执行完成' - doesn't wait for execution to complete), which is valuable. However, it doesn't mention what happens after starting (e.g., how to track progress via 'get_task_status'), error handling, authentication needs, or rate limits. For a mutation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (8 Chinese characters) with zero wasted words. It's front-loaded with the core purpose and includes the key behavioral characteristic. Every character earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'success' means for an async operation, how to monitor the task afterward, potential side effects, or error scenarios. Given the sibling tools include status/log retrieval functions, the description should reference these for 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 description coverage is 100%, so the schema already fully documents the single parameter 'task_id'. The description adds no additional parameter information beyond what's in the schema. Baseline 3 is appropriate when schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('异步启动任务' - asynchronously start a task) and resource ('任务' - task), with the specific behavioral characteristic of not waiting for completion. However, it doesn't distinguish this from its sibling 'run_task', which presumably runs tasks synchronously.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like 'run_task' (synchronous execution) or 'run_subscription'. There's no mention of use cases, prerequisites, or trade-offs between asynchronous and synchronous execution.
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. While '查询' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns paginated results, or what format the output takes. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any redundant words or unnecessary elaboration. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns a list of tasks. It doesn't explain what information is included in the task list, how results are structured, or any error conditions. For a read operation with no structured output documentation, more context is needed.
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 0 parameters with 100% schema description coverage, so the schema already fully documents the input requirements. The description doesn't add parameter details (which isn't needed here), but it implies no filtering or options are available, aligning with the empty schema. This meets the baseline for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('查询' meaning 'query') and resource ('青龙面板中的所有定时任务列表' meaning 'all scheduled tasks in Qinglong panel'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_task_status' or 'get_task_logs', which prevents 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 Guidelines2/5
Does 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 like 'get_task_status' or 'run_task'. It lacks explicit context about use cases, exclusions, or prerequisites, leaving the agent to infer usage from the tool name alone.
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 provided, the description carries the full burden of behavioral disclosure. It states the tool queries lists, implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, returns paginated results, or details the output format. This is a significant gap for a tool with zero annotation coverage.
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, efficient sentence that directly states the tool's purpose without any wasted words. It's front-loaded and appropriately sized for a simple list operation, earning its place by clearly conveying the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given 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) and lack of annotations, the description is incomplete. It doesn't explain what the output looks like (e.g., list format, data structure), behavioral aspects like error handling, or how it fits with siblings. For a tool with no structured data to rely on, more context is needed.
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 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. Baseline is 4 for zero parameters, as it avoids unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('查询' meaning 'query' or 'list') and resource ('青龙面板中的所有订阅列表' meaning 'all subscription lists in Qinglong panel'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'list_qinglong_tasks', which also lists items from the same system, so it misses full 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 Guidelines2/5
Does 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 prerequisites, context for usage, or compare it to sibling tools like 'run_subscription' or 'list_qinglong_tasks', leaving the agent to infer usage based on the name alone.
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 provided, the description carries the full burden. It discloses that the tool waits for completion (up to 30 seconds) and returns execution logs, which is useful. However, it lacks details on permissions needed, error handling, what happens if the task exceeds 30 seconds, or whether it's idempotent, which are critical for a mutation tool.
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 concise and front-loaded, stating the core action and key constraint (30-second wait) in a single sentence. There's no wasted text, but it could be slightly more structured by separating the action from the behavioral details for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a task execution tool with no annotations and no output schema, the description is incomplete. It doesn't cover error cases, return format details beyond '执行日志', or interaction with sibling tools, leaving gaps for an AI agent to understand full behavior.
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 schema description coverage is 100%, with the parameter 'task_id' clearly documented as '任务 ID'. The description doesn't add any additional meaning beyond the schema, such as format examples or constraints, so it meets the baseline for high schema coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('执行任务并等待完成') and the resource ('任务'), specifying that it runs a task and waits for completion. It distinguishes from sibling 'run_task_async' by explicitly mentioning synchronous waiting, but doesn't fully differentiate from other task-related tools like 'get_task_logs' or 'get_task_status' in terms of scope.
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 you need to run a task and wait for its completion, with a 30-second timeout. However, it doesn't explicitly state when to use this vs. alternatives like 'run_task_async' (for asynchronous execution) or 'get_task_status' (for checking status without running), leaving some ambiguity in tool selection.
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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