flin-google-keyword-planner-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.2.6
Disambiguation5/5
Each tool has a clearly distinct purpose: OAuth flow tools handle different stages (authorization URL, code exchange, status, local server), and keyword tools use distinct seed types (keyword+URL, keywords, site, URL, historical). No ambiguity between any pair.
Naming Consistency5/5
All tools follow a consistent snake_case pattern. OAuth tools use the prefix 'google_ads_' followed by a verb_noun describing the action (e.g., authorization_url, exchange_authorization_code). Keyword tools uniformly start with 'keyword_ideas_from_' and specify the seed type. This consistent structure helps agents predict naming.
Tool Count5/5
9 tools is well-scoped for a Google Ads Keyword Planner MCP. It covers authentication setup (4 tools) and keyword idea generation from multiple seed types (5 tools), without unnecessary duplication. The count feels appropriate for the domain.
Completeness5/5
The tool set covers the full OAuth lifecycle (authorization, exchange, status, local flow) and provides all common ways to generate keyword ideas: from keywords, URL, site, and historical data. There are no obvious gaps for the stated purpose of keyword planning.
Average 2.7/5 across 9 of 9 tools scored. Lowest: 2/5.
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
- Last stable release on August 4, 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.
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.json to 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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only states it generates ideas without revealing behavioral traits such as read-only nature, side effects, or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence) but lacks necessary detail, making it under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 11 parameters, no parameter explanations, and no mention of the output schema (which exists), the description is far from complete for effective tool usage.
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%. The description does not explain any of the 11 parameters, leaving the agent without understanding of their purpose or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies generating keyword ideas using SiteSeed, but it lacks clarity on what SiteSeed is and does not differentiate from sibling tools like keyword_ideas_from_keywords or keyword_ideas_from_url.
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 over alternatives. The description does not mention when to use SiteSeed vs other keyword idea generation methods.
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 must fully disclose behavior, but it only says 'Generate keyword ideas using KeywordSeed.' It does not reveal safety traits, prerequisites, or side effects. For a tool with 11 parameters, this is insufficient.
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 very short at one sentence, which is concise but lacks structural elements like front-loading key info. It is under-specified for a tool with many parameters and sibling tools.
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 no annotations, a rich schema with 11 parameters, and existing output schema, the description is incomplete. It does not explain the impact of parameters like location, language, or network on results, nor does it clarify what the output contains.
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%, meaning the input schema provides no parameter descriptions. The description adds no meaning for any of the 11 parameters, so it fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Generate keyword ideas using KeywordSeed' which indicates the tool generates keyword ideas from keywords, but it lacks a specific verb and resource distinction. It does not differentiate from sibling tools that also generate keyword ideas from other inputs like URLs.
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 usage guidelines are provided. The description does not specify when to use this tool over alternatives like keyword_ideas_from_url or keyword_ideas_from_site, leaving the agent without context for selection.
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 responsibility for behavioral disclosure. It fails to mention side effects, pagination behavior, rate limits, or authentication needs. The output schema exists but the description adds no behavioral context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-specified for a tool with 12 parameters. Conciseness should not sacrifice completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high complexity (12 params, 0% schema coverage, no annotations, similar siblings), the description is severely incomplete. It lacks guidance on parameter usage, behavioral traits, and differentiation, making it inadequate for correct agent 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%, so the description must compensate. It does not explain any parameter, not even the required keywords and url, offering no semantic value beyond the schema's minimal 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?
The description 'Generate keyword ideas using KeywordAndUrlSeed' clearly states the verb (generate) and resource (keyword ideas), and the seed type is implied by the tool name. However, it does not differentiate from sibling tools like 'keyword_ideas_from_keywords' which uses only keywords, missing a chance to clarify the unique combination.
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 provided on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or context where this seed type is preferred, leaving the agent without decision support.
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 present, and the description lacks any behavioral details such as whether the tool is read-only, requires authentication, has rate limits, or what side effects occur. The agent has no insight beyond 'generate'.
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 and front-loaded. However, it is too brief given the tool's complexity, sacrificing necessary information for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high parameter count (11), no schema descriptions, no annotations, and the existence of sibling tools, the description is severely incomplete. It fails to cover usage, parameter roles, or return values, leaving the agent with insufficient context to use the tool correctly.
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 should compensate by explaining key parameters. It only implies the 'url' parameter via the tool's name and description, but ignores the other 10 parameters (e.g., customer_id, language_id, filters). This adds minimal semantic value.
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 action ('generate') and the output ('keyword ideas') and specifies the source ('UrlSeed'). However, it does not differentiate from sibling tools like 'keyword_ideas_from_keywords' or 'keyword_ideas_from_site', leaving ambiguity about when to use this URL-based variant.
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 the siblings (e.g., when a URL-only input is available). No usage context, prerequisites, or examples are 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?
With no annotations, the description carries full responsibility. It only states the action (create URL) but omits behavioral details like side effects, required permissions, rate limits, or error conditions. It does not disclose that this is a read-only operation generating a URL.
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 earns its place in terms of brevity but is too sparse for a tool with two parameters and sibling context.
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's complexity (OAuth URL generation) and the presence of an output schema, the description should explain the output or setup requirements. It does not mention what the URL contains or how to use the result, leaving gaps in understanding.
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 coverage is 0%, so the description must explain parameters. However, it does not mention 'state' or 'redirect_uri' at all, leaving the agent unaware of their roles or default values. The description adds no value over 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 states the tool creates a Google OAuth consent URL specifically for generating a Google Ads refresh token. It uses a specific verb ('Create') and resource ('OAuth consent URL'), and the purpose is distinct from sibling tools like google_ads_exchange_authorization_code or google_ads_oauth_status.
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 provided on when to use this tool versus its siblings (e.g., google_ads_exchange_authorization_code, google_ads_start_local_oauth_flow). It does not indicate prerequisites or context, such as needing client credentials first.
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, and the description does not disclose behavioral traits such as read/write nature, rate limits, or authentication requirements, leaving significant gaps.
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 very concise (one sentence), but this brevity comes at the cost of omitting necessary details for a complex tool.
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's complexity (16 params, 5 required, many optional), the description is insufficient; it does not cover the breadth of functionality or parameter roles.
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 and 16 parameters, the description only mentions the date-range concept, failing to explain the many other parameters (e.g., keywords, location, network).
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 generates keyword ideas and specifies 'historical metrics options' with a date range, distinguishing it from siblings that focus on different sources.
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 lacks guidance on when to use this tool over siblings, only hinting at historical data without explicit comparison or exclusion criteria.
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 fully disclose behavior. It omits critical details: does it block waiting for callback? What happens on port conflict? Does it open browser? Lifespan of server? These are important for an agent invoking this tool.
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, front-loaded. However, it sacrifices necessary detail for brevity. Loses a point for omitting important info that could be added without bloat.
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 complexity of OAuth flow and absence of schema descriptions, description is insufficient. Lacks details on error handling, state, and expected behavior for multiple invocations. Though output schema exists, description itself is incomplete.
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 description does not explain the 'redirect_uri' parameter at all. Agent cannot infer its purpose (e.g., where the callback should be sent) or default value significance.
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 the tool starts a local OAuth callback server and returns the Google consent URL, using specific verbs and resource. It distinguishes itself from sibling tools like 'google_ads_authorization_url' which likely just returns the URL without starting a server.
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 (e.g., as first step in OAuth flow) or when not to use alternatives. Does not mention prerequisites or ordering with siblings like 'google_ads_exchange_authorization_code'.
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 must carry full behavioral burden. It lacks details on side effects (e.g., storing the refresh token), required permissions, error states, or rate limits. The description is too minimal for a security-sensitive 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?
Single sentence that is front-loaded and contains no fluff. Every word adds value.
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 having an output schema, the description lacks context about prerequisites, the flow sequence, error handling, and security implications. For a complex OAuth operation, more completeness is needed.
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 coverage is 0% and description adds no explanation for the 'code' or 'redirect_uri' parameters. The description only mentions 'authorization code' generically without mapping to the parameter.
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 clear verb ('Exchange') and identifies the specific resource (authorization code) and outcome (session refresh token). It effectively distinguishes this step from sibling tools like google_ads_authorization_url or google_ads_oauth_status.
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. Missing prerequisites (e.g., must have obtained an authorization code first) and no mention of when not to use it.
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 fully disclose behavior. It only states what is returned, not whether the operation is read-only or has side effects. Given the simplicity, a score of 2 is appropriate.
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, clear sentence with no unnecessary words. It is front-loaded with the key verb and resource.
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 has no parameters and an output schema exists, the description sufficiently indicates what the tool returns. Additional context about the OAuth flow might be helpful but is not required.
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?
There are no parameters (0), so the baseline is 4. The description adds no parameter info, which is acceptable since none exist.
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 'Return' and the resource 'local OAuth callback status and whether a runtime token is available'. It is distinct from sibling tools that handle authorization URL generation or code exchange.
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 checking OAuth status but lacks explicit when-to-use or when-not-to-use guidance. No comparison with sibling tools is provided.
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

flin-google-keyword-planner-mcp MCP server

Copy to your README.md:

[![flin-google-keyword-planner-mcp MCP server](https://glama.ai/mcp/servers/flin-agency/flin-google-keyword-planner-mcp/badges/card.svg)](https://glama.ai/mcp/servers/flin-agency/flin-google-keyword-planner-mcp)

Score Badge

Copy to your README.md:

[![flin-google-keyword-planner-mcp MCP server](https://glama.ai/mcp/servers/flin-agency/flin-google-keyword-planner-mcp/badges/score.svg)](https://glama.ai/mcp/servers/flin-agency/flin-google-keyword-planner-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/flin-agency/flin-google-keyword-planner-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server