cleanuparr-mcp

Server Quality Checklist

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Latest release: v0.2.1
Disambiguation5/5
Each of the 8 tools represents a distinct functional area: cleaner configuration, health status, jobs, events, stats, arr/download clients, feature configs, and notifications. The sub-operation names further clarify boundaries, leaving no ambiguity about which tool to use for a given task.
Naming Consistency5/5
All tools follow a consistent `cleanuparr_<area>` snake_case pattern, and sub-operations use a uniform verb_noun structure (get_, list_, update_, delete_, create_, etc.). The only minor deviation is the compound `arr_download_clients`, but it is still clear and does not break the overall naming scheme.
Tool Count5/5
With 8 well-categorized tools, the server is well-scoped. Each tool groups a coherent set of operations, making the count neither too thin nor too heavy for the domain of managing a Cleanuparr instance.
Completeness5/5
The surface covers the key entities and actions: CRUD for arr instances, download clients, notification providers, and rules; configuration get/update for all major settings; job lifecycle management; event and strike retrieval/management; and statistics. No critical operations appear to be missing for the server's stated purpose.
Average 4/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 15 commits in the last 12 weeks
- Last stable release on August 13, 2026
- 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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}
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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 full burden. It discloses important behavioral traits for some operations: purge_strikes is 'irreversible', update_general_config warns about resetting unspecified fields in a read-modify-write, and secret placeholders for apiKey/password are noted. However, many operations (e.g., create, delete, test) lack side-effect or permission details, so the disclosure is partial.
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 long but appropriately so for 15 operations. It is front-loaded with the usage pattern and then organized as a clean bulleted list of operations, each on a single line. There is no fluff or redundancy; every line adds operational detail. The structure is easily scannable for an agent needing to find a specific operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (15 operations) and lack of annotations, the description provides substantial context: function signatures, DTO fields, and behavioral warnings. The presence of an output schema reduces the need to describe return values. Some operations are under-descripted (e.g., cleanuparr_get_arr_config has no explanatory text), but the names and signatures largely suffice. Overall, it is fairly complete for a multi-operation dispatch tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only provides `operation` and a free-form `arguments` object with no internal structure. The description compensates fully by giving a function signature for each operation (e.g., cleanuparr_create_arr_instance(arr_type, instance)) and, for many, listing DTO fields (e.g., 'enabled, name, url, apiKey'). This directly tells the agent how to construct the arguments dict for any operation, adding critical meaning beyond the schema.
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 states it covers 'cleanuparr arr download clients operations' and then enumerates 15 distinct operations with clear verbs (create, delete, list, test, update, purge) and resources (arr instances, download clients). This clearly communicates the tool's scope and differentiates it from sibling tools that cover other Cleanuparr domains, though it is a collection rather than a single specific verb+resource.
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 explains how to invoke the tool ('Pass `operation` and an `arguments` dict') but does not explicitly state when to use this tool versus alternatives. It lacks any 'when to use' guidance, exclusions, or references to sibling tools, leaving the selection decision to the agent's inference from the operation list.
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 behavioral burden. It discloses some useful traits: secret fields may be redacted, update 'Replaces' a provider, delete is destructive. But it does not mention permissions, reversibility, rate limits, or potential side effects of testing a provider.
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 compact and front-loaded with the key guidance about operation and arguments. The bullet list is scannable, each line earning its place with a concise operation summary and parameters. There is no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-operation dispatcher, the description covers all operations with enough detail to select correctly. The presence of an output schema means return values do not need to be explained. Minor gaps include no error behavior or explicit arguments dict structure, but overall it is adequate.
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?
Schema coverage is 0%, so the description must compensate. It does so by listing operation-specific parameter names like provider_type, provider, and provider_id, and by noting common fields (name, isEnabled, event flags) plus provider-specific DTOs. This adds real meaning beyond the generic top-level schema, though it stops short of fully documenting the provider object's required structure.
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 identifies the tool as 'cleanuparr notifications operations' and enumerates six specific operations (create/delete/list/test/update providers, apprise status). This distinguishes it from sibling tools focused on other Cleanuparr domains. It lacks a single verb+resource formulation, but the operation list provides concrete purpose.
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?
It instructs users to pass an operation and matching arguments dict, and each operation has a one-line summary. However, it does not explicitly state when to use this tool over sibling tools, nor does it provide exclusions like 'for jobs use cleanuparr_jobs'. Usage context is implied rather than explicit.
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 indicates mutating vs. read-only through operation names (create, delete, update) and notes one behavioral quirk ('Priority is ignored by the upstream update'). However, it does not disclose side effects, reversibility, or prerequisites, leaving significant gaps for a config tool with many mutating operations.
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 long but justified by the need to document 19 sub-operations. It is well-structured as a bulleted list with each line containing the function name and its arguments/fields, making it scannable. The opening sentence provides the general pattern, and every line adds usable information, though the length is substantial.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high tool complexity (19 operations), sparse schema, and no annotations, the description covers all operations and their parameters. An output schema exists, so return values are not needed. However, it lacks contextual details such as how to obtain required GUIDs (e.g., download_client_id) or any mention of error conditions, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines 'operation' (an enum) and a generic 'arguments' dict, providing zero detail about parameters. The description fully compensates by explaining that 'arguments' must match the operation's parameters, then listing parameter names and DTO fields for each of the 19 operations. This provides complete semantic meaning beyond the schema.
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 this tool performs Cleanuparr cleaner config operations and enumerates all 19 supported operations with explicit verbs (create, delete, get, list, update). It distinguishes from sibling tools (health status, jobs, events, etc.) by focusing on config management, though it is a dispatcher rather than a single action.
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?
Usage is implied by the listed operations (e.g., to create a queue rule, call cleanuparr_create_queue_rule), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions. The overloaded nature of the tool (single operation parameter) makes context implicit rather than explicit.
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 of behavioral disclosure. It adds useful constraints such as 'Seeker cannot be manually triggered' and describes the replace semantics for update_job_schedule, but it omits details on auth requirements, side effects, or error conditions.
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 concise and well-structured, using a bulleted list to break down each operation. Each line is short, focused, and free of unnecessary verbiage, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all five operations and highlights a key constraint (Seeker cannot be triggered manually), but it does not fully specify the shape of the JobSchedule DTO needed for start_job and update_job_schedule. While an output schema exists, the input-side ambiguity for complex operations makes the description only partially complete.
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?
With the schema providing zero coverage for the arguments dictionary, the description compensates by naming the parameters for each operation (job_type, schedule) and listing the enumerable job_type values. It references JobSchedule DTO but does not detail its structure, leaving some ambiguity for constructing valid schedule objects.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies this tool as handling cleanuparr jobs operations and enumerates five distinct sub-operations (get, list, start, trigger, update) with precise wording. This differentiates it from sibling tools focused on other Cleanuparr resources such as config, health, or stats.
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 the tool is for managing Cleanuparr jobs through its operation list, but it does not provide explicit context on when to use this tool versus alternatives, nor does it state any exclusions. Usage is inferred rather than guided.
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?
With no annotations, the description must disclose behavior itself. It uses the word 'Replace' for all update operations, signaling overwrite semantics, and lists affected fields. However, it does not warn that omitted fields in the arguments might be cleared, nor mention any permissions or side effects beyond the replacement.
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 well-structured, starting with the usage pattern and then a bullet list of operations. Each bullet is concise and informative, with no redundant text, making it easy to scan and front-loaded with key instructions.
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?
The tool has six operations with custom argument structures, but the description only hints at the fields for each. The arguments schema is permissive (any object), so it doesn't validate. Without a detailed argument list per operation, an agent cannot reliably construct valid calls, making the description incomplete despite having an output schema.
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?
Schema description coverage is 0%, so the description compensates. It defines the operation parameter via the enum and instructs the arguments dict to match the operation. For updates, it lists key fields like enabled, blacklistPath, per-arr settings, and Seeker toggles, though not exhaustive for every operation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it handles Cleanuparr feature configs and enumerates six specific operations for three distinct configs (blacklist sync, malware blocker, Seeker). It distinguishes these from sibling tools that manage cleaner configs, health, jobs, events, stats, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides a concrete usage pattern: pass an operation and a matching arguments dict, and lists each operation's purpose. It does not explicitly compare to sibling tools or state when not to use it, but the context is clear enough for selection.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful constraints (page_size capped at 500, count capped at 50, deprecated v1 stats not exposed, default values). However, it does not disclose side effects of mutating operations like delete_strikes or resolve_manual_event, nor does it mention authentication, rate limits, or error behavior. This is a clear gap for a tool with write operations.
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 long but appropriately structured as a bulleted list of operation signatures. The opening sentence explains the dispatch pattern, and each line is compact and self-contained. There is no fluff; every line adds necessary operational detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (18 operations) and the presence of an output schema, the description covers the dispatch mechanism, parameters, defaults, and key constraints. It does not explain return values (covered by output schema) but also omits error handling and side-effect warnings, which would be valuable for a dispatcher with mutating operations.
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 input schema only defines 'operation' as an enum and 'arguments' as a generic object with no additional properties. The description compensates by listing each operation's parameters, defaults, types (e.g., ISO-8601 dates), and caps. This is essential for constructing correct invocation arguments and goes well beyond the schema, though it does not fully document every parameter's type or allowed values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it handles 'cleanuparr events operations on Cleanuparr' and enumerates 18 specific operations with verbs like delete, get, list, and resolve targeting events, strikes, and stats. This distinguishes it from sibling tools focused on config, health, jobs, and stats by its event-specific scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for event and strike operations and provides usage instructions for each sub-operation, including required arguments and default values. It does not explicitly contrast with alternatives, but the operation list and naming make the appropriate context clear. It also notes API caps and date formats, which guide correct invocation.
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 burden. It adds useful behavioral context by noting which operations are anonymous (e.g., 'anonymous liveness' at /health) and which are authenticated ('authenticated detailed health report'). However, it does not explicitly state that these are read-only or describe potential side effects, though health checks are inherently non-destructive.
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 compact bullet list with front-loaded operation names and short, informative descriptions. Every line is purposeful, and the format makes the tool easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (not shown) and a clear list of operations, the description adequately covers scope. It provides enough detail to understand each operation's purpose and arguments, and the output schema can handle return-value specifics.
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?
Schema coverage is 0%, but the description compensates by listing each operation with its expected arguments (e.g., cleanuparr_run_health_check accepts check_id). The generic 'arguments' dict is clarified by the operation-specific signatures, providing meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as handling 'cleanuparr health status operations' on Cleanuparr, with a specific list of operations. This distinguishes it from sibling tools focused on cleaner config, jobs, events, stats, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by listing health-related operations and noting the resource (Cleanuparr). It does not explicitly mention alternatives or exclusions, but the scope is clear enough for an agent to select this tool for health status checks.
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?
Annotations declare readOnlyHint=true, and the description's operations are all get/list, aligning with this. The description adds value beyond the annotation by detailing the dispatcher pattern, parameter defaults, and special notes like 'episode_id is used for Sonarr episode history' and 'search_status can contain repeated enum filters.' No contradictions found.
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 structured as a scannable bulleted list, with each operation given a concise purpose and parameter list. It is long due to the number of sub-operations, but every line provides necessary information without fluff. The opening sentence effectively frames the dispatcher pattern.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 sub-operations, many parameters) and that the schema provides no descriptions, the description covers all operations and their parameters, making the tool's interface quite clear. It does not explain return values, but the output schema likely covers that. Some parameter enums (e.g., search_status values) are not fully specified, but overall comprehensive.
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?
With 0% schema description coverage, the description compensates by listing each operation's parameters and defaults in function-signature form, which adds meaning beyond the schema's generic 'arguments' object. It also highlights operation-specific behavior for certain parameters, though it does not enumerate all enum values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies this as a dispatcher for Cleanuparr stats operations, and enumerates each supported operation with a specific verb and resource (e.g., 'Get score history for an item', 'Get custom-format score tracking statistics'). This differentiates it from sibling tools focused on config, health, jobs, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage instructions by explaining the operation/arguments pattern and listing each operation's signature with parameters and defaults. While it does not explicitly mention when not to use the tool or name alternative tools, the context is clear that this is the stats/read-only dispatcher, so usage is well implied.
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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