flin-google-ads-mcp

Server Quality Checklist

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Latest release: v0.1.3
Disambiguation5/5
Each tool targets a distinct resource or action: searching vs listing customers, retrieving specific entities (campaigns, ad groups, ads, keywords), performance insights, health check, and account listing. No significant overlap.
Naming Consistency4/5
Tools predominantly use verb_noun snake_case (e.g., get_campaigns, list_accessible_customers). 'health_check' deviates slightly but remains clear and conventional.
Tool Count5/5
9 tools is well-scoped for a Google Ads MCP, covering essential read operations and utility functions without overwhelming or under-serving the domain.
Completeness4/5
The tool set provides thorough read-only coverage of core Google Ads entities (campaigns, ad groups, ads, keywords, insights) and account management. Missing write operations, but the server appears focused on querying.
Average 2.9/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 commits in the last 12 weeks
- No stable releases found
- 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.
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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, and the description does not disclose behavioral traits such as read-only nature, authentication needs, or rate limits. It only states a generic fetch action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it lacks structure. It is not overly long, but for a 4-parameter tool, it is too minimal to be effective.
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 has 4 parameters and an output schema, the description fails to explain what campaigns are, how filtering works, or what the output contains. It is incomplete for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and no mention of parameters in the description, the agent gains no insight into the meaning of customer_id, status, limit, or login_customer_id beyond their names and types.
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 'Get campaigns for a customer account,' indicating the action and resource. However, it does not differentiate from sibling tools like get_ad_groups or get_ads, lacking specificity.
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 on when to use this tool versus alternatives. The description provides no context for when to use it over siblings like find_customer_clients or get_insights.
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 provided. Description only says 'Find', implying a read operation, but does not disclose any behavioral traits such as authentication requirements, rate limits, or side effects.
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?
Single sentence of 9 words is concise and front-loaded. However, brevity sacrifices crucial detail.
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?
With 8 parameters, no annotations, and an output schema present, the description provides minimal context. It does not explain the purpose of most parameters or the nature of the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. Description only hints at 'manager account' and 'descriptive name', covering 2 of 8 parameters. Leaves 6 parameters unexplained, forcing reliance on schema property names.
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?
Description clearly states 'find subaccounts by descriptive name under a specific manager account', giving a specific verb and resource. It distinguishes from sibling tool 'get_customer_clients' by implying a search/filter function.
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 on when to use this tool versus alternatives like 'get_customer_clients'. No mention of prerequisites or context for invocation.
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 must disclose all behavioral traits. It only mentions data retrieval with optional filtering, lacking details on side effects, permissions, rate limits, or output behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it sacrifices completeness. While front-loaded, it does not fully utilize the space to add value for the agent.
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?
Despite an output schema existing, the description fails to explain the tool's behavior sufficiently for 5 parameters. Missing parameter guidance and usage context make it inadequate for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only hints at campaign_id filtering. It does not explain the other four parameters (customer_id, login_customer_id, status, limit), leaving the agent with minimal information beyond basic schema names.
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 retrieves 'ad groups' for a 'customer account', with optional filtering by campaign. It uses a specific verb and resource, differentiating it from sibling tools like get_ads or get_campaigns.
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 on when to use this tool versus alternatives. The description simply states what it does without providing context on preferred scenarios or exclusions.
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 full burden but only states it 'lists subaccounts'. It fails to disclose important behaviors such as default parameter values, pagination via 'limit', filtering options (status, direct_only, include_hidden, include_self), or any side effects. The agent lacks crucial operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it sacrifices necessary detail. It could include more context without being verbose, especially given the 7-parameter schema and sibling tools. It is not front-loaded with critical information.
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 has 7 parameters and no parameter descriptions in the schema, the description is insufficiently complete. While an output schema exists, the lack of parameter explanations and behavioral cues means the agent cannot effectively use the tool without external knowledge. The description needs to cover the role of key parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no explanation for any of the 7 parameters. Parameters like 'customer_id', 'status', 'direct_only', etc., are not mentioned, leaving their semantics entirely unclear. The tool name and description do not even hint at the filtering capabilities.
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 ('List subaccounts') and the resource ('customer_client') with a specific context ('under a manager account'). It differentiates from the sibling 'find_customer_clients' by implying a straightforward listing rather than a search.
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 its sibling 'find_customer_clients' or other tools. It does not mention prerequisites, limitations, or context for use, leaving the agent to infer.
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 provided, so the description must carry full burden. It only states 'Get' implying read-only, but doesn't disclose pagination behavior, filtering capabilities, or any potential side effects. Missing details on what 'performance metrics' are included.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, but overly terse. While concise, it sacrifices necessary detail for a tool with 9 parameters and no schema descriptions.
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?
With 9 parameters and an output schema, the description does not explain what the tool returns or how filtering works. It is insufficient for an agent to correctly invoke without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 9 parameters with 0% description coverage. The description adds no explanation for parameters like customer_id, campaign_id, date_range, etc., relying entirely on the schema which lacks 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 clearly states the tool retrieves 'keyword-level entities and performance metrics', specifying the resource (keywords) and data type (performance metrics). It differentiates from siblings like 'get_ad_groups' or 'get_ads' by focusing on keywords.
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 on when to use this tool versus alternatives. The description lacks context for selecting it among siblings like 'get_insights' or 'get_campaigns'.
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 provided, so description carries the burden. It discloses that login_customer_id is ignored, which is helpful. However, it does not state if the operation is read-only, safe, or any potential side effects. The output schema exists, so return format is covered externally.
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?
Two concise sentences with no fluff. The first sentence defines purpose immediately; the second adds a key behavioral note. Could be slightly improved by more front-loading, but it is effective.
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?
With an output schema, return values are covered. However, the description omits explanation for the limit parameter, which is essential for controlling result size. The behavioral note is useful, but overall completeness is average.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description should explain parameters. Only login_customer_id is mentioned (as ignored). The limit parameter, though optional with a default, is not described at all, leaving the agent without guidance on its purpose.
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 tool lists customer IDs accessible by OAuth credentials. The verb 'List' and resource 'customer IDs' are specific. However, it does not differentiate from siblings like find_customer_clients or get_customer_clients, which might serve similar purposes.
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 on when to use this tool versus alternatives. The note about login_customer_id being ignored is a behavioral detail, not usage context. Sibling tools exist but no comparison is provided.
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 provided, so description must cover behavioral traits. Only states 'Get ads' (read operation), but does not disclose pagination, rate limits, authentication needs, or response structure. Lacks depth for a safe agent invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 12 words, front-loaded with action verb. No redundant information.
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?
Tool has 6 parameters with no required ones, plus output schema; description lacks details on status, limit, login_customer_id, and authentication context. Incomplete for effective use despite conciseness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%; description only explains campaign_id and ad_group_id filters. No explanation for customer_id, status, limit, or login_customer_id. Status default 'ALL' is undefined. Minimal value added beyond 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 states the verb 'get', resource 'ads', and scope 'for a customer account', with optional filters. It distinguishes from sibling tools like get_ad_groups and get_campaigns.
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 on when to use this tool vs alternatives (e.g., get_ad_groups, get_campaigns). It mentions optional filters but doesn't provide context for when to use specific parameters or exclude others.
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?
Describes the tool as read-only, indicating no side effects, but lacks details on auth needs, rate limits, or pagination behavior.
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 a single concise sentence, but could be slightly expanded to include parameter guidance without losing efficiency.
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 tool with 7 parameters and no schema descriptions, the description is too brief, omitting details about metric types, time range usage, and output interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description only partially explains the 'level' parameter, leaving most parameters (customer_id, date_range, etc.) undocumented.
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 retrieves read-only performance metrics at campaign, ad_group, or ad level, distinguishing it from sibling tools that fetch entity lists.
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 implies usage for performance data but does not explicitly state when not to use it or provide alternatives among 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?
No annotations provided. The description only states 'check' without disclosing outcomes, side effects, or error conditions. Lacks behavioral detail for a zero-param 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?
Single sentence, front-loaded, no unnecessary words. Efficiently conveys purpose.
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 zero params and presence of output schema, the description is mostly complete. However, behavioral details are missing, slightly reducing completeness.
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?
No parameters exist, so schema coverage is 100%. Description adds no param info, but baseline for 0 params is 4.
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 ('check') and identifies the resource ('Google Ads configuration' and 'client initialization'). It clearly distinguishes from sibling tools that retrieve data.
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 as a preliminary check but does not explicitly state when to use or alternatives. Implied context from siblings but no direct guidance.
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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