Gemini MCP Tool
Server Quality Checklist
Latest release: v1.1.8
- Disambiguation4/5
Tools have distinct purposes: ask-gemini for general interaction with edit capability, brainstorm for creative idea generation, fetch-chunk for retrieving continuation of long responses. Some overlap in text generation but descriptions clarify boundaries.
Naming Consistency2/5Naming is inconsistent: 'ask-gemini' and 'fetch-chunk' use hyphens, 'brainstorm' is one word, while 'Help' is capitalized and 'ping' is lowercase. No consistent verb_noun pattern across all tools.
Tool Count4/5With 5 tools, the server covers core interaction, creative brainstorming, and chunk retrieval. Slightly thin but well-scoped for a focused Gemini assistant.
Completeness3/5Covers basic chat, creative idea generation, and long response handling, but lacks tools for managing sessions, listing models, or more advanced capabilities. Moderate completeness for its scope.
Average 3/5 across 5 of 5 tools scored. Lowest: 1.9/5.
See the Tool Scores section below for per-tool breakdowns.
- 9 of 11 community issues answered or closed in the last 6 months
- 9 commits in the last 12 weeks
- Last stable release on
- 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.jsonto 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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The one-word description 'Echo' discloses no behavioral traits, such as whether it performs a side effect, returns data, or has prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
While extremely short, the description is under-specified to the point of being unhelpful. Conciseness should not come at the cost of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema and no annotations, the description must at least state the return behavior. 'Echo' alone is incomplete and leaves the agent guessing about the tool's effect.
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 100% for the single parameter 'prompt', with a clear description 'Message to echo'. The tool description adds no additional meaning beyond the schema, so baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Echo' is vague and essentially a tautology with the name. It doesn't specify a clear verb or resource, and it doesn't distinguish the tool from siblings like 'ask-gemini' or 'fetch-chunk'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings. The description provides no context about appropriate use cases or 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 provided, so description must bear full burden. It mentions sandbox for safe testing but does not disclose whether edits are applied or if the tool is read-only. Behavioral traits like side effects or permissions are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and somewhat cryptic with flags. It is concise but not well-structured or informative enough.
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?
With 6 parameters, no output schema, and no annotations, the description is too brief. It fails to explain core functionality, return values, or usage patterns, leaving significant gaps.
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?
The input schema has 100% description coverage, so the baseline is 3. The description adds minimal value beyond mentioning flags, as the schema already explains parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description mentions options like model selection, sandbox, and changeMode, but does not clearly state the core action of the tool (asking Gemini). It is vague and fails to distinguish it from siblings like brainstorm or Help.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 about appropriate 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 provided, the description carries full responsibility for behavioral disclosure. It only states 'receive help information', implying a non-destructive read operation, but fails to detail any side effects, authentication needs, or response behavior. This 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.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is efficient, but lacks necessary detail. It is not overly verbose, but the conciseness comes at the cost of clarity and completeness.
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 the lack of output schema and the simplicity of the tool, the description is too minimal. It does not explain what kind of help is provided, how to receive it, or what the output looks like. A help tool typically expects some indication of topics or format.
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, so the schema coverage is 100% by default. The description adds no parameter-level meaning, but the baseline for 0-parameter tools is 4, as no parameter documentation is needed. The description does not add value but also does not detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'receive help information' is a vague restatement of the tool name 'Help' without specifying scope or topics. It offers no additional context beyond the name, making it barely adequate for distinguishing from sibling tools like ask-gemini or fetch-chunk.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 alternatives such as ask-gemini or brainstorm. There is no mention of prerequisite conditions or preferred contexts, leaving the agent to infer usage from the name alone.
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?
With no annotations, the description carries full burden and discloses key behaviors: dynamic context gathering, creative frameworks, domain integration, clustering, analysis, and iterative refinement. This gives a good sense of how the tool operates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a dash and list, keeping it concise and front-loading the purpose. Could be slightly more structured but effectively minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 8 parameters, no output schema, and no annotations, the description covers the main features and behaviors reasonably well. Missing some details like output format or limitations, but adequate for a creative tool.
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 100% with all parameters described, so the description adds little beyond high-level context. The description mentions 'domain context integration' which aligns with the domain parameter, but does not deepen understanding.
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 explicitly states 'Generate novel ideas' (verb and resource) and lists creative frameworks and features, clearly distinguishing it from sibling tools like ask-gemini which is for Q&A.
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 for brainstorming sessions but provides no explicit guidance on when to use this tool versus alternatives, nor any conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It indicates a read operation (retrieves) but does not disclose potential side effects or cache persistence. The description is adequate but could benefit from mentioning if chunks are cleared after retrieval.
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 extremely concise with two sentences, front-loading the purpose and immediate usage context. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description sufficiently covers the purpose, usage context (subsequent chunks after partial response), and parameter roles. No critical information is missing.
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?
Both parameters ('cacheKey' and 'chunkIndex') are fully described in the schema (100% coverage). The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves cached chunks from a changeMode response, with specific verb and resource. It distinguishes itself from siblings like 'ask-gemini' and 'brainstorm' by specializing in chunk retrieval.
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?
The description explicitly instructs to use this tool 'to get subsequent chunks after receiving a partial changeMode response,' providing clear context. However, it lacks explicit when-not or alternative guidance, though the context implies it's for follow-up retrievals.
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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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.
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