adsense-mcp
Server Quality Checklist
Latest release: v0.1.1
- Disambiguation5/5
Each tool targets a distinct operation: listing accounts, retrieving a specific account, and generating reports. There is no overlap between these actions, and the report tool even auto-discovers the account, reducing ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with the 'adsense_' prefix (list_accounts, get_account, generate_report). This makes the naming predictable and easy to navigate.
Tool Count4/5With 3 tools, the server is on the lower end of the ideal range, but it covers the core AdSense operations: account listing, account retrieval, and report generation. The count feels minimal yet sufficient for a focused server, though slightly thin.
Completeness3/5The surface covers essential account and reporting operations, but lacks other common AdSense resources like ad units, sites, or alerts. This might be a notable gap for agents needing broader management capabilities, though it may be acceptable for a report-focused server.
Average 3.6/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 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.
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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 provided, the description carries the full burden of disclosing side effects. It only says 'get', implying a read-only operation, but does not explicitly confirm it is non-destructive, nor does it mention permission requirements, error behavior, or return value characteristics. The minimal disclosure is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with an example, containing no filler. Every word adds value and it is front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema), the description covers the basics but omits details like return value structure, error handling (e.g., what happens if account doesn't exist), and any authentication or permission notes. Since there is no output schema, explaining what is returned would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It indirectly explains the 'account' parameter by saying 'by resource name' and gives an example format ('accounts/pub-123'), which clarifies the required pattern. However, it does not explicitly name the parameter or explain its full semantics (e.g., must start with 'accounts/'), leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Get one AdSense account by resource name' with a specific example. It distinguishes from siblings (adsense_list_accounts for multiple, adsense_generate_report for reporting) by focusing on retrieving a single account by its resource identifier.
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?
Usage is implied through the phrase 'by resource name' and the example, but there is no explicit guidance on when to use this tool versus alternatives like list_accounts. It does not state when not to use it or mention prerequisites (e.g., need a known account resource name).
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 states the tool lists accounts, which is a read operation, but does not disclose any behavioral traits such as authentication requirements, rate limits, or whether it returns all accounts or only those with certain statuses. The description is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that fully conveys the tool's purpose. There is no wasted text, and it is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema, no annotations), the description is mostly complete. However, it could benefit from mentioning what the response contains (e.g., account IDs, names) or any prerequisites like authentication, but the lack of complexity makes this a minor gap.
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?
The tool has zero parameters, and schema description coverage is 100% (vacuously). The description adds no parameter details because there are none, but it correctly implies no inputs are needed. Baseline for 0 params is 4, and the description is adequate.
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 clearly states the tool lists AdSense accounts for the authenticated user, using a specific verb and resource. It distinguishes from siblings like adsense_get_account (which likely retrieves a single account) and adsense_generate_report (which generates reports), though it doesn't explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (listing accounts for the authenticated user) but does not explicitly state when to use this tool versus alternatives. It doesn't mention exclusions or alternatives, but the purpose is clear enough that an agent can infer when to use it.
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 behavioral burden. "Extract" implies a read-only data fetch, and "Account is discovered automatically when omitted" is a useful behavioral detail. However, it does not disclose response format, pagination behavior, permissions, or any side effects, leaving a meaningful transparency gap.
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?
Two front-loaded sentences say exactly what is needed without fluff. The first sentence gives the purpose, the second tells the caller what to supply and clarifies account optionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 12 parameters, no output schema, and no annotations, this description is too thin. It does not say what the report response looks like, whether results are paginated, or how ad-hoc complexity is handled. The auto-discovery note is helpful, but the tool still lacks guidance for an agent to fully anticipate the invocation outcome.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75%, and the description adds a high-level parameter map: dimensions, metrics, filters, dates, sorting, and other report parameters. It also notes the API version, which helps normalize parameter syntax. It does not detail every uncovered parameter such as limit, currencyCode, or languageCode, but the schema still provides most semantics.
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 a specific verb and resource: "Extract any ad-hoc AdSense report." It clearly distinguishes this reporting tool from the sibling account tools by framing it as report extraction with flexible parameters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear context: use this tool for ad-hoc AdSense reporting where the caller supplies dimensions, metrics, filters, dates, and sorting. It also removes a common prerequisite by noting that the account is discovered automatically when omitted. It does not explicitly compare to sibling alternatives, but the usage context is clear.
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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