Gmail MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation3/5
There is overlap between gmail_list_messages and gmail_search_messages, as both retrieve messages with filtering, though search offers more specific criteria. Similarly, gmail_send_message and gmail_send_message_with_attachment are nearly identical except for the attachment parameter. This could cause agent confusion.
Naming Consistency5/5
All tool names follow a consistent 'gmail_verb_noun' pattern in snake_case. Every name clearly indicates the action and resource, e.g., gmail_list_messages, gmail_get_message, gmail_send_message.
Tool Count5/5
With 8 tools, the server covers essential Gmail operations without being overwhelming. The count is well-scoped for a focused MCP server, providing a balanced set of capabilities.
Completeness4/5
The tool set covers core email operations: send, receive, list, search, mark read, delete, and stats. Missing features like label management and draft handling are minor gaps, but the current surface supports primary workflows effectively.
Average 3/5 across 8 of 8 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
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fails to disclose whether deletion is permanent, moves to trash, requires specific scopes, or affects conversations; only states 'delete' without added detail.
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?
Very brief but under-specified; the args/returns structure is clean, but the conciseness comes at the cost of missing critical information.
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?
No annotations or output schema, and the description omits essential details like permanence, batching limits, error handling, and return value interpretation, leaving the agent underinformed.
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%; description merely restates the parameter type (list of message IDs) with no explanation of how to obtain IDs, format, or constraints, providing no value beyond 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?
Clearly states 'Delete Gmail messages', specific verb+resource, and distinct from sibling tools like gmail_list_messages or gmail_mark_as_read.
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 marking as read or moving to trash; lacks context on prerequisites or irreversibility.
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 exist, so the description bears full burden. It mentions returning a dictionary with details or error but omits authentication needs, rate limits, or that it is a read operation.
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 short and structured with Args and Returns, but it is too brief given the lack of annotations and schema descriptions; each sentence could convey more.
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 no output schema and no annotations, the description lacks details on return format, error cases, or practical usage context like required scopes.
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 coverage, the description only restates 'message_id: Gmail message ID', adding no extra semantics about format, constraints, or how to obtain the ID.
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 gets details of a specific Gmail message, distinguishing it from siblings like list, search, or delete. However, it does not specify what 'details' include.
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 provided. The description does not mention when to use this tool over alternatives (e.g., search) or any prerequisites like having a valid message ID.
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-only nature, authentication needs, or rate limits. It only states the return type as a dictionary.
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 with two sentences, but it lacks depth. It front-loads the purpose but could be more informative without significant length increase.
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?
The description omits key details such as which specific statistics are returned, the format of the dictionary, and any prerequisites. This leaves the agent with incomplete information for correct invocation.
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?
The description adds minimal value over the input schema; 'Include unread message count' is nearly identical to the schema title 'Include Unread'. No additional details on default behavior or impact on output are given.
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 name and description clearly state 'Get Gmail account statistics', which is a specific verb and resource. It distinguishes itself from sibling tools that deal with individual messages.
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 like gmail_list_messages or gmail_search_messages. The description merely states what it does without context.
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 does not disclose behavioral traits such as rate limits, size limits, asynchronous behavior, or error handling. For a mutation tool, this is a significant gap.
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 concise with a clear structure: one-liner verb, then args list, then return value. The first sentence is informative. No wasted words, though the 'Returns' line is vague.
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 5 parameters, no output schema, and no annotations, the description should provide more context about the return dictionary, error handling, and usage scenarios. The sibling tool with attachment is mentioned but not differentiated. The description feels like a basic doc rather than comprehensive guidance.
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?
The description adds meaning beyond the schema by describing each parameter (to, subject, body, cc, bcc) and noting that cc/bcc are comma-separated. With 0% schema description coverage, this is valuable, though it doesn't specify format for 'to' (single email vs multiple) or body content type.
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 'Send a Gmail message' with a clear verb+resource. It distinguishes from sibling tools like gmail_send_message_with_attachment by omission, implying it sends without attachments. However, it could be more specific about supported body formats (plain text vs HTML).
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., gmail_send_message_with_attachment). No prerequisites (e.g., authentication, sending limits) are mentioned. The description only lists parameters without context.
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 carry the full burden of behavioral disclosure. It states the return format but does not disclose that the operation is read-only, idempotent, or safe. It lacks details on side effects, rate limits, or resource consumption. For a list operation, basic safety traits are expected.
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 extremely concise: one sentence explaining purpose, followed by a compact parameter list and return format. Every element is necessary and contributes meaning. There is no redundant or filler content.
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 low complexity (2 parameters, no output schema), the description is incomplete. It does not explain default behavior (e.g., what messages are returned when no query is given), pagination, ordering, or limitations. The mention of 'message data' in returns is vague, and the sibling tools suggest potential overlap that is not disambiguated.
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?
The input schema has no property descriptions (0% coverage), so the description adds significant value by providing concrete examples for the 'query' parameter (e.g., 'from:sender@example.com') and specifying the valid range for 'max_results' (1-100). This helps the agent form correct queries.
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 Gmail messages and allows an optional search query. However, it does not differentiate from the sibling 'gmail_search_messages' tool, which may have similar functionality. The verb 'List' and resource 'Gmail messages' are specific.
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 alternatives like 'gmail_search_messages'. It does not specify prerequisites (e.g., authentication, mailbox) or exclusions. The agent is left to infer usage from the tool name alone.
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 does not disclose idempotency, permissions, side effects, or behavior for invalid message IDs.
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?
Short description with Args and Returns sections, but the Args section is redundant with the schema; overall no unnecessary content.
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?
Adequate for a simple operation given no output schema, but lacks details on error handling, idempotency, or confirmation of success.
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%; the description merely restates the parameter name ('message_ids') without adding format, constraints, or usage details beyond 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 the action ('Mark'), resource ('Gmail messages'), and state ('as read'), distinguishing it from sibling tools like gmail_delete_messages.
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; no prerequisites or exclusions mentioned.
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 must disclose behavioral traits. It only states the action and arguments, lacking details on authentication, attachment size limits, error handling, or side effects. This is insufficient for an AI agent to understand the full 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 concise with a front-loaded purpose sentence followed by a brief argument list. Every sentence is necessary, though the argument list could be integrated more succinctly. Still, it is well-structured for quick comprehension.
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 that sends emails with attachments, the description is incomplete. It lacks details on return value format (only 'Dictionary with send result'), attachment handling specifics, or potential constraints (e.g., file size limits, supported file types). Given no output schema and 0% parameter schema coverage, more context is needed.
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?
Given 0% schema description coverage, the tool description adds basic semantics for each parameter (e.g., 'to: Recipient email address'). However, it omits validation rules, formatting requirements, or edge cases, providing only minimal meaning beyond the parameter 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 'Send Gmail message with attachment,' specifying the verb (send) and resource (Gmail message) with a distinguishing feature (attachment). This effectively differentiates it from the sibling tool 'gmail_send_message' which presumably sends without attachment.
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 when to use the tool (when an attachment is needed) but does not explicitly state conditions or exclusions compared to alternatives like gmail_send_message. No guidance on prerequisites or context 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?
With no annotations, the description must fully disclose behavior. It only states 'Returns: Dictionary with search results', lacking details on return structure, pagination, rate limits, or authorization requirements. This is insufficient for a search 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?
The description is efficiently structured with a short intro, a bulleted Args list, and a Returns line. Every sentence adds value, and the format is easy to parse. No redundant or misleading content.
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 7 parameters and no output schema, the description does not fully describe the return value (vague 'Dictionary with search results'), no mention of error handling, pagination, or result limits beyond max_results. Missing critical context for a robust search tool.
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?
The schema has 0% description coverage, so the description's Args section provides essential meaning for all 7 parameters. Each parameter gets a brief but clear explanation (e.g., 'Filter by sender email', 'YYYY/MM/DD format'). While more detail could be provided, it compensates well for the schema gap.
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 searches Gmail messages with specific criteria. This verb+resource combination is distinct from sibling tools like gmail_list_messages (likely listing without advanced filters) and gmail_get_message (retrieving by ID).
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 like gmail_list_messages or gmail_get_stats. The description does not mention any prerequisites, exclusions, or comparison with sibling tools.
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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