revenuecat-mcp

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct operation: fetching subscriber info, checking a specific entitlement, retrieving offerings, granting/revoking entitlements, and deleting subscribers. The purposes are clearly separated with no meaningful overlap.
Naming Consistency5/5
All tool names follow the consistent verb_noun snake_case pattern (e.g., get_subscriber, grant_entitlement, revoke_entitlement). This makes the API predictable and easy to navigate.
Tool Count5/5
Six tools is a well-scoped number for a subscription management server. Each tool serves a clear purpose without redundancy or unnecessary bloat.
Completeness4/5
The server covers the core read and write operations for subscriber and entitlement management. Minor gaps exist such as lack of subscriber attribute updates or bulk listing, but the essential lifecycle is well represented.
Average 3.5/5 across 6 of 6 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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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?
With no annotations, the description carries the full burden for behavioral disclosure. It only states a basic action and provides no information about side effects, reversibility (though revoke_entitlement exists), idempotency, permissions, or what happens if the user already has the entitlement. This is a significant gap 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence with no redundancy. It front-loads the action and key object, 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?
This is a mutation tool with no annotations and no output schema. The description is too minimal to understand the complete behavior: it does not mention return values, error cases, idempotency, or preconditions. Given the complexity (3 parameters, enum), the description should offer more operational context.
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 already provides 100% parameter coverage, with clear descriptions for app_user_id, entitlement_id, and duration (including an enum). The description adds no additional semantic value beyond the schema, so the baseline score of 3 applies.
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 uses a specific verb ('Grant') with a resource ('promotional entitlement') and target ('to a user'), plus a scope ('for a specified duration'). It clearly distinguishes from siblings like revoke_entitlement, check_entitlement, and get_offerings.
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?
No guidance is given on when to use this tool versus alternatives. While the phrase 'promotional entitlement' implies a certain use case, the description does not mention exceptions, prerequisites, or explicitly contrast with revoke_entitlement or other sibling tools.
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 carries the disclosure burden. It implies a read operation via 'Get' but does not state whether it is read-only, what happens for unknown users, authentication needs, or the exact structure of returned data. Minimal behavioral context beyond the verb.
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, focused sentence that names the operation and its key outputs. No wasted words or redundancy.
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 tool is simple with one parameter and no output schema. The description lists the returned categories but lacks details on error behavior, relationship to check_entitlement, or use-case boundaries. Adequate for basic selection but incomplete for confident invocation in novel situations.
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 coverage is 100% for the single parameter app_user_id, which is described as 'The app user ID to look up.' The tool description does not add extra context about parameter usage, so it meets the baseline but adds no additional semantic value.
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 the verb (Get) and the resource (subscriber info, entitlements, subscription status) for a user. It effectively distinguishes from siblings like grant_entitlement and revoke_entitlement, which are mutations, and get_offerings, which targets offerings rather than subscriber state.
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 offers no guidance on when to use this tool versus alternatives like check_entitlement. It does not mention exclusions or provide context for choosing this over siblings, leaving the agent to infer usage.
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 carries the burden of explaining side effects. It does disclose the cascading behavior of deleting purchase history, which is important. However, it does not explicitly state that the action is irreversible, whether it cancels subscriptions, or any permission requirements. 'Use with caution' is a general warning but lacks specific behavioral context.
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: one sentence stating the core action and a short warning. Every word is necessary and front-loaded. It delivers the essential information without redundancy.
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 destructive nature (no annotations, no output schema), the description is incomplete. It lacks crucial information about irreversibility, potential side effects on subscriptions/entitlements, and any prerequisites or permissions. It also does not position itself relative to sibling tools like revoke_entitlement, which is a key alternative. While the tool is simple, the one-paragraph description does not sufficiently prepare an agent for a destructive action.
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% (app_user_id is described as 'The app user ID to delete.'), so the baseline is 3. The tool description adds no additional meaning about the parameter, such as format, constraints, or examples, so it does not exceed the baseline.
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 the action: 'Delete a subscriber and all their purchase history.' This is a specific verb+resource, and it distinguishes itself from sibling tools like grant_entitlement or get_subscriber by being the only tool that deletes a subscriber entirely.
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?
No explicit guidance is provided on when to use this tool versus alternatives. The phrase 'Use with caution' implies careful usage but does not say when to use it, when not to use it, or mention any alternative tools. With siblings like revoke_entitlement, it would be helpful to state that this is for permanent deletion as opposed to revoking access.
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 disclosure responsibility. It adds the meaningful detail that the entitlement must be 'active', which is a behavioral condition. However, it does not explicitly state return type, side effects (though likely read-only), or any error/edge-case behavior. For a simple check tool, this is adequate but not rich.
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, front-loaded sentence that conveys the core purpose immediately. There is no fluff or repetition. Every word earns its place.
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?
Given the tool's simplicity (2 params, no output schema, no annotations), the description is minimal but lacks an explicit statement of return value or behavior on invalid input. It checks if an entitlement is active, but does not clarify whether the response is a boolean, a status object, or something else. A more complete description would specify the return format.
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 baseline is 3. The description adds a small amount of value by providing concrete examples of entitlement IDs ('premium', 'pro'), which clarifies the expected format beyond the schema's generic 'The entitlement identifier to check.'
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 the tool's function: checking if a user has an active entitlement. The verb 'check' is specific and the resource 'entitlement' is well-defined. It implicitly distinguishes itself from sibling tools like grant_entitlement and revoke_entitlement (which modify entitlements) and get_subscriber (which fetches broader subscriber data).
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 explicit guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or other tools. Usage is only implied by the function name and description, but there is no direct comparison to siblings.
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 carries the full burden and only states the action. It does not disclose side effects, permissions, reversibility, or return behavior for this mutation operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words.
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 tool is simple with full schema coverage, but without an output schema or annotations, the description offers minimal context and does not mention what happens after revocation or any edge cases.
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 covers 100% of parameters, and the description adds context by specifying 'promotional entitlement,' which clarifies the type of entitlement_id expected beyond the generic schema descriptions.
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 uses a specific verb ('revoke') with a clear resource ('promotional entitlement'), and it effectively distinguishes itself from sibling tools like grant_entitlement and check_entitlement.
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 for revoking promotional entitlements but does not explicitly state when to use it versus alternatives or provide exclusions.
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. 'Fetch' clearly implies a read-only operation, but the description does not mention potential errors, authorization requirements, or whether an empty list is returned for an invalid user ID. Basic safety is communicated, but richer behavioral context is lacking.
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, concise sentence that is front-loaded with the verb and resource. Every word is useful and there is no redundancy or fluff.
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?
The tool is simple (one parameter, no output schema, no annotations), and the description clearly states what is fetched ('available subscription offerings and packages') for a user. This is adequate for an agent to understand the tool's purpose and expected return, though explicit return format details are not provided.
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 already documents the single parameter 'app_user_id' with a clear description, so schema coverage is high (100%). The description does not add any additional parameter semantics beyond what the schema provides, so a baseline score of 3 is appropriate.
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 uses the specific verb 'Fetch' and specifies the resource 'available subscription offerings and packages for a user,' clearly distinguishing this from sibling tools like get_subscriber or check_entitlement. The purpose is unambiguous and unique.
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 context that this tool retrieves offerings/packages for a specific user, which distinguishes it from the entitlement and subscriber sibling tools. It does not explicitly state when not to use it, but the context is clear enough for an agent to select it appropriately.
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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