gsc-mcp

Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: health check, URL inspection, sitemap listing, site listing, and three levels of analytics (general, top pages, top queries). No overlap that would confuse an agent.
Naming Consistency5/5
All tools follow a consistent 'gsc_underscore' pattern with descriptive names (e.g., gsc_health_check, gsc_inspect_url, gsc_top_queries). No mixing of conventions.
Tool Count5/5
7 tools cover key Search Console functionalities (health, inspection, sitemaps, sites, analytics) without being excessive. The scope is well-mapped to the domain.
Completeness3/5
Common read operations are present, but write/mutate tools are missing (e.g., no submit or delete sitemap, no request indexing, no site removal). This creates notable gaps for complete lifecycle management.
Average 4.2/5 across 7 of 7 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
- Last stable release on April 25, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds minimal extra behavioral context beyond being a convenience wrapper. No additional disclosure of data lag or limits beyond schema.
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?
Three sentences, no unnecessary words, front-loaded with the core purpose. Appropriately sized for the tool complexity.
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 existence of an output schema and detailed schema parameter descriptions, the description is complete enough for an agent to decide when to use this tool and what to expect.
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 parameter descriptions already cover site_url, days, limit, and response_format sufficiently. The tool description does not add additional meaning or usage hints beyond what is in the 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 it returns top N search queries for a site over a recent period, using specific verbs and resources. It distinguishes itself from the sibling tool gsc_query_search_analytics by being a convenience wrapper for quick rankings.
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?
Explicitly recommends use for quick ranking and weekly SEO check-ins, and notes it is a wrapper over gsc_query_search_analytics, implying alternatives for more detailed analysis. Does not explicitly state when not to use, but context is clear.
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 already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint, so the description adds specific output details (status, error counts) without contradiction. This is appropriate given the annotation richness.
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 three sentences long, with the main action front-loaded. The use case list is efficient and adds value without fluff. Each sentence earns its place.
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 simplicity (one required parameter, output schema exists, annotations are thorough), the description covers purpose and usage well. However, it misses guidance on parameter format, relying on the schema which has minimal description. Still largely complete.
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%, but the description does not explain the parameters (site_url or response_format). The site_url parameter has a minimal schema description referencing another tool, but the overall lack of parameter guidance in the description is insufficient.
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 starts with a clear verb-resource pair: 'List every sitemap registered for a property'. It specifies output fields (status and error counts) and distinguishes from siblings like gsc_list_sites by focusing on sitemaps. The title in annotations reinforces the purpose.
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 explicitly lists three use cases (verifying acceptance, spotting parse errors, confirming submission dates). While it doesn't mention when not to use or alternative tools, the use cases provide concrete guidance for when to invoke this tool.
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 already declare readOnlyHint, idempotentHint, etc. The description adds context about being a diagnostic check that tests authentication and API reachability, which complements the annotations without contradiction.
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?
Three sentences, front-loaded with purpose, no wasted words. Every sentence adds value.
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's simplicity (diagnostic with one optional param), annotations cover safety, and output schema exists, the description provides sufficient context for an AI agent to correctly invoke and interpret the tool. Sibling tools further differentiate.
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?
Only one optional parameter (response_format) with enum values defined in schema. Schema description coverage is 0%, so the description should add meaning. However, it does not mention the parameter or explain its impact (e.g., markdown vs json output). The parameter is simple but the description should still clarify how it affects behavior.
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 'Diagnostic: confirm the OAuth token is valid and the Search Console API is reachable.' It uses specific verbs and resources, and distinguishes from sibling tools that perform specific operations (e.g., gsc_inspect_url, gsc_query_search_analytics).
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?
Explicitly advises to 'Run this first when setting up the server or after errors to determine whether the issue is auth, network, or a specific site.' This provides clear context for when to use it. Could be improved by stating when not to use, but it's still strong.
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 already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context about rate limits and the scope of returned data (everything the Inspect URL panel shows), without contradicting annotations.
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 (6 sentences) and front-loaded: first sentence states the verb+resource, then lists outputs, use cases, and rate limit. Every sentence adds value without redundancy.
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 rich annotations and output schema presence, the description covers the main behavioral traits (rate limits, scope) and use cases. It could mention the output format (returns markdown or JSON), but the usage context is sufficiently complete for a diagnostic tool.
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 includes descriptions for all parameters (site_url, inspection_url, language_code, response_format), so schema coverage is high. The tool description does not add additional parameter-level details beyond the schema, meeting the baseline of 3.
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 runs the URL Inspection API for a specific page and enumerates what it returns (indexing verdict, coverage state, etc.). It differentiates from sibling tools that focus on queries or pages, making its purpose distinct.
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?
Provides explicit use cases: diagnose ranking issues, confirm indexing after publish, spot canonical mismatches. Also mentions rate limit (~2000 calls per day) and hints at a future bulk tool, giving guidance on 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, non-destructive, idempotent. The description adds context about the returned table format and the critical siteUrl prefix detail, which is beyond annotations. No contradictions.
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?
Three concise sentences: purpose, return value, key usage tip. No unnecessary words, front-loaded with the action.
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 description covers the main purpose and a critical usage detail (siteUrl format). Given that an output schema exists (from context) and the tool is simple, it is nearly complete. Could mention potential edge cases like empty results.
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 has a single parameter with a nested object. The schema description for 'response_format' is clear, but the tool description does not mention this parameter. Since schema coverage is low (0%), the description should compensate; it does not, so a 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 clearly states the tool lists every Google Search Console property the authenticated user can access, returns a table with URLs and permissions, and distinguishes itself from sibling tools by highlighting the importance of the exact siteUrl format.
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 implicitly guides when to use (before other GSC tools) by stating to use the returned siteUrl for other tools, but does not explicitly compare with siblings or mention when not to use.
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 already declare readOnly, idempotent, nondestructive. The description adds that it is a convenience wrapper, explaining the internal chaining. No contradictions.
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?
Two sentences: first states purpose, second adds usage guidance. No redundancy, front-loaded, every sentence earns its place.
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 description covers purpose, usage, and relationship to sibling. An output schema is indicated but not shown; given the simplicity and annotations, it is complete enough.
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 provides clear descriptions for all parameters (site_url format, days lookback, limit number, response_format output). The description adds no extra parameter details beyond what the schema already conveys.
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', the resource 'top N landing pages', and the scope 'for a site over a recent period'. It differentiates from siblings like gsc_top_queries by calling itself a wrapper over gsc_query_search_analytics.
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 explicitly says it's a convenience wrapper over gsc_query_search_analytics and advises using it to spot top and underperforming URLs. While it doesn't explicitly state when not to use, the context implies the underlying tool for more control.
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 already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds return metrics (clicks, impressions, CTR, avg position) and mentions flexibility, but no behavioral contradictions. Description adds value beyond annotations.
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?
Two brief paragraphs front-loaded with purpose and usage guidance. No redundant information. Every sentence serves a 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 the tool's flexibility and the presence of an output schema, the description covers the essential aspects: purpose, when to use, return values. Could mention pagination or default date range, but schema covers those. Adequate for a complex tool.
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 has detailed descriptions for each parameter, so description doesn't need to cover them. It hints at 'multi-dimensional grouping' and 'non-default search types' which relate to dimensions and search_type parameters, but doesn't add significant new meaning.
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 runs a flexible Search Analytics query. It distinguishes itself from siblings by specifying that it is for multi-dimensional grouping and non-default search types, referencing convenience tools gsc_top_queries and gsc_top_pages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'For common cases, prefer the convenience tools... Use this tool when you need multi-dimensional grouping or non-default search types.' This clearly tells when to use and when not to use.
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

Copy to your README.md:

[![gsc-mcp MCP server](https://glama.ai/mcp/servers/jayrockliffe-defused/gsc-mcp/badges/card.svg)](https://glama.ai/mcp/servers/jayrockliffe-defused/gsc-mcp)

Score Badge

Copy to your README.md:

[![gsc-mcp MCP server](https://glama.ai/mcp/servers/jayrockliffe-defused/gsc-mcp/badges/score.svg)](https://glama.ai/mcp/servers/jayrockliffe-defused/gsc-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/jayrockliffe-defused/gsc-mcp'

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