qbittorrent-readonly-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct monitoring concern: aggregate health, general torrent listing, per-torrent details, problem triage, and size/inactivity analysis. The two list-like tools are clearly differentiated by filtering to problem torrents versus all torrents.
Naming Consistency5/5All tool names follow a consistent snake_case verb_noun pattern (get_*, list_*, analyze_*). There are no mixed conventions or vague one-word identifiers.
Tool Count5/5Five tools is a well-scoped set for a read-only qBittorrent monitoring server. Each tool provides a distinct capability without redundancy.
Completeness4/5The surface covers the main read-only workflow: health summary, listing, details, problem identification, and size analysis. Minor gaps exist around lower-level details like trackers or peer lists, but agents can accomplish core monitoring without dead ends.
Average 3.6/5 across 5 of 5 tools scored. Lowest: 2.8/5.
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.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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?
Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false). The description adds that filters are applied locally, but the phrase 'no filter value is sent as an arbitrary API endpoint' is vague and potentially confusing. No contradiction with annotations.
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 brief and the main verb/resource is front-loaded, which is good. However, the second clause is cryptic and does not earn its place, and the overall terseness borders on under-specification rather than deliberate 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?
With five optional parameters, zero schema descriptions, and sibling tools that perform related listing/filtering tasks, the description is too sparse. It does not explain what the returned output contains, how filters interact, or when this tool is preferable to list_problem_torrents or analyze_largest_torrents.
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%, so the description must compensate for the five undocumented parameters, but it only says 'using local filters' without explaining limit, state, category, min_size_gib, or inactive_days. The parameter names are somewhat self-explanatory, but the description adds essentially no parameter-level meaning.
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 states the verb ('List') and resource ('torrents') clearly, and the phrase 'using local filters' signals that filtering is done client-side. However, the second clause about arbitrary API endpoints is confusing and does little to distinguish this tool from siblings like get_torrent_details or list_problem_torrents.
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 is given for when to use this tool versus alternatives such as get_torrent_details, list_problem_torrents, or analyze_largest_torrents. The 'local filters' hint implies a listing use case, but there are no exclusions, prerequisites, or decision rules.
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?
Annotations already communicate read-only, idempotent, and non-destructive behavior. The description adds useful selection semantics (size-based ordering and the inactivity-age filter) but does not disclose details such as how results are capped or ordered beyond the word 'largest'.
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 entire description is one front-loaded sentence with no filler. Every phrase contributes either the core behavior or the optional filter.
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 the simple two-parameter schema, the presence of an output schema, and annotations that cover safety/idempotency, the description covers the essential behavior. It is only missing explicit sibling differentiation and a more concrete statement of the limit parameter's effect.
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?
With 0% schema description coverage, the description must compensate, and it does clarify inactive_days as a 'minimum inactivity age'. However, the limit parameter is not explained; its meaning is only implied by the word 'largest' and the schema's default of 20.
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 uses a specific verb and resource: 'Return the largest torrents', with an optional inactivity-age filter. It uniquely identifies the tool's role among siblings through the 'largest' qualifier, though it does not explicitly contrast it with list_torrents.
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 when-to-use or when-not-to-use guidance is provided, and no alternatives are named. An agent is left to infer that this should be chosen over list_torrents or list_problem_torrents based solely on the phrase 'largest torrents'.
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?
The annotations already disclose readOnly, idempotent, and non-destructive behavior, so the description does not repeat that. It adds filtering scope, but provides no extra behavioral context such as pagination, ordering, or result size details beyond the schema's default limit.
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 filler. It conveys the action and the precise inclusion criteria efficiently, 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.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity, read-only tool with no required parameters, an output schema, and clear annotations, the description is nearly complete. The main omission is guidance on the limit parameter, but the schema default and output schema mitigate the impact.
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%, and the description says nothing about the 'limit' parameter. The parameter name and default value suggest the basic meaning, but the description does not clarify how limiting behaves, such as whether results are truncated or how a custom limit affects the response.
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 uses a specific verb, 'List', and identifies a distinct resource: problem torrents, explicitly naming the statuses included (missing, errored, unknown, or incomplete stalled/stopped). This clearly differentiates it from the generic sibling list_torrents.
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 wording implies this tool is for finding torrents in problematic states, especially stalled or stopped ones, rather than for general listing. However, it does not explicitly mention sibling alternatives or state conditions for when this tool should not be used.
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?
Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to repeat safety properties. It adds a little context with the list of returned aggregates, but no extra behavioral disclosures such as auth or failure modes.
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?
One compact sentence with a strong verb and a clear list of result categories. No redundant qualifiers or filler.
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 parameterless read-only health summary with an output schema and full annotations, the description covers everything needed to invoke it. It does not need to elaborate on return layout since the schema exists.
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 no parameter documentation is required; the schema coverage is effectively complete. The description's mention of returned fields avoids any need to compensate for parameter gaps.
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 opens with 'Return' and names versions, transfer speeds, task state counts, and a problem summary, making the resource and scope clear. The system-level content clearly separates it from torrent-scoped siblings like list_torrents and analyze_largest_torrents.
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 when-to-use or alternative-selection guidance is given. The description only states what is returned; it does not say when to prefer get_health_summary over get_torrent_details or list_problem_torrents.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds little behavioral detail beyond the hash-prefix input requirement; 'safe' is redundant with the annotations.
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?
One sentence with no filler. The primary action and scope are front-loaded, and the input format requirement is stated compactly.
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?
The tool is simple: one parameter, clear annotations, and an output schema that can cover return values. The main missing piece is guidance on when to use this tool instead of siblings, but that is not critical for a single-parameter lookup.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain the opaque 'identifier' parameter. It does so clearly by specifying that it is an 8+ character hexadecimal Info Hash prefix, giving the agent a precise format to validate against.
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 a specific verb ('get'), a specific resource ('details for one torrent'), and the required input form ('8+ character hexadecimal Info Hash prefix'). It distinguishes itself from sibling list/analysis tools by emphasizing single-torrent scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for one torrent' implies the tool is appropriate when a single torrent's details are needed, but there is no explicit guidance about when not to use it or which sibling to prefer. Usage context is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/XiaotaoGuo/qbittorrent-readonly-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server