Email SMTP/IMAP MCP Server

by samihalawa

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: email_respond handles replies/forwards, email_send creates new emails, emails_find searches, emails_modify changes states, and folders_list enumerates folders. The descriptions reinforce these distinct roles, making tool selection unambiguous.
Naming Consistency4/5
The naming is mostly consistent with a verb_noun pattern (e.g., email_send, emails_find, folders_list), but there is a minor deviation with email_respond (verb_noun) versus emails_modify (plural_noun_verb). This small inconsistency slightly reduces predictability but remains readable.
Tool Count5/5
With 5 tools, the server is well-scoped for email management. Each tool earns its place by covering core email operations: sending, replying, searching, modifying, and listing folders. This count is appropriate and avoids bloat or thin coverage.
Completeness4/5
The tool set provides strong coverage for email workflows, including CRUD-like actions (send, find, modify) and folder management. A minor gap is the lack of a tool for creating or deleting folders, but agents can still handle most email tasks effectively with the available tools.
Average 3.2/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions HTML support and file attachments, but fails to address critical aspects like authentication requirements (account_name parameter), rate limits, delivery guarantees, error handling, or whether this is a synchronous or asynchronous operation. For a mutation tool with significant impact, this is inadequate.
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 appropriately concise with two sentences. The first sentence states the core functionality, and the second provides usage examples. There's no unnecessary repetition or fluff. However, it could be slightly more front-loaded with key behavioral information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an 8-parameter mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after sending (success/failure indicators, message IDs), doesn't address authentication or permission requirements, and provides minimal guidance on when to use alternatives. The schema does heavy lifting, but the description should compensate for missing behavioral context.
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 description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds minimal value beyond the schema - it mentions HTML support (implied by body_type enum) and file attachments (covered in schema). No additional syntax, format, or constraint details are provided beyond what's in the structured fields.
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's purpose: 'Send a new email with HTML support and file attachments.' It specifies the verb ('send') and resource ('email'), and distinguishes it from siblings like email_respond (reply) and emails_modify (edit). However, it doesn't explicitly differentiate from emails_find (search) beyond the 'new' qualifier.
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 provides implied usage guidance: 'Use this to send messages, project updates, or any new email conversation.' This suggests it's for initiating conversations rather than replying (email_respond) or modifying existing emails (emails_modify). However, it lacks explicit when-not-to-use instructions or clear alternatives for edge cases.
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 the full burden of behavioral disclosure. It mentions 'flexible filters' and optional content/attachments but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, or what the return format looks like (e.g., list structure, pagination). For a search tool with 6 parameters, this leaves 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 concise and front-loaded, with the core purpose stated in the first sentence. The second sentence adds usage examples without redundancy. However, the examples could be more tightly integrated, and there's room to eliminate minor wordiness (e.g., 'Use this to' is slightly verbose).
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 complexity (6 parameters, nested objects) and lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error conditions, or behavioral constraints, which are crucial for a search tool with filtering options. The agent would struggle to use this effectively without guessing at missing context.
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 description adds minimal parameter semantics beyond the schema, which has 100% coverage. It mentions 'flexible filters' and 'optionally get full email content and attachments,' hinting at the 'filters,' 'include_content,' and 'include_attachments' parameters, but doesn't provide additional context like search syntax or performance implications. Given the high schema coverage, the baseline of 3 is appropriate.
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's purpose as 'Search for emails in your inbox with flexible filters' and mentions 'find specific emails, check for unread messages, or browse your inbox.' It specifies the verb (search/find) and resource (emails/inbox) but doesn't explicitly differentiate from sibling tools like 'emails_modify' or 'folders_list' beyond the search focus.
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 provides implied usage through examples ('find specific emails, check for unread messages, or browse your inbox') but lacks explicit guidance on when to use this tool versus alternatives like 'email_respond' or 'email_send.' It doesn't mention prerequisites or exclusions, leaving the agent to infer 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 carries the full burden of behavioral disclosure. While it mentions actions like 'move between folders' and 'mark emails as read', it doesn't address critical behavioral aspects such as whether changes are reversible, what permissions are required, if there are rate limits, or what happens when conflicting parameters are provided (e.g., mark_read and mark_unread both true).
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 appropriately sized with two sentences that are front-loaded with the core purpose. The second sentence provides helpful examples without redundancy, though it could be slightly more structured by separating usage scenarios.
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 (7 parameters, mutation operations) and lack of annotations and output schema, the description is insufficient. It doesn't explain return values, error conditions, or behavioral nuances like how multiple state changes interact, leaving significant gaps for an AI agent to understand the tool fully.
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 description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'move between folders' and 'flag important emails', which slightly reinforces parameter purposes but doesn't provide additional syntax, format details, or usage constraints.
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's purpose with specific verbs ('change email states like read/unread, flagged, or move between folders') and identifies the resource (emails). It distinguishes from sibling tools like email_send or email_respond by focusing on modification rather than creation or response, though it doesn't explicitly differentiate from all siblings.
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 provides implied usage context with examples ('organize your inbox, mark emails as read, archive messages, or flag important emails'), but lacks explicit guidance on when to use this tool versus alternatives like email_respond or folders_list. No exclusions or prerequisites are 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 carries the full burden of behavioral disclosure. It mentions listing folders and organizing emails, but fails to disclose critical traits such as whether this requires authentication, rate limits, or how the output is structured (e.g., pagination, error handling). This leaves significant gaps for an agent to understand the tool's 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 appropriately sized with two sentences that are front-loaded and efficient. The first sentence states the purpose clearly, and the second adds context without redundancy, making it easy to parse with minimal waste.
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?
Given the tool's low complexity (2 parameters, no output schema, no annotations), the description is somewhat complete but lacks depth. It covers the basic purpose and usage but omits behavioral details like authentication needs or output format, which are important for a tool with no annotations or output schema to rely on.
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 100% description coverage, clearly documenting both parameters ('account_name' and 'include_counts'). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 without adding or detracting 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 tool's purpose with a specific verb ('List') and resource ('email folders/labels'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'emails_find' or 'emails_modify', which prevents a perfect score.
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 provides implied usage guidance by mentioning 'to see your folder structure and organize emails', which suggests when this tool might be useful. However, it lacks explicit guidance on when to use this versus alternatives like 'emails_find' for searching emails, leaving room for ambiguity.
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 the full burden of behavioral disclosure. While it mentions the core action (reply/forward), it doesn't describe important behavioral traits like whether this sends the email immediately, requires specific permissions, has rate limits, or what happens on failure. For a mutation tool with 9 parameters, this leaves significant gaps in understanding how the tool behaves beyond basic functionality.
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 perfectly concise with two sentences that each earn their place. The first sentence states the core functionality, and the second provides usage context. There's no wasted text, and the information is front-loaded with the essential action.
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?
Given the tool's complexity (9 parameters, mutation operation) and lack of both annotations and output schema, the description is minimally adequate. It covers the basic purpose and usage context but doesn't address behavioral aspects, error conditions, or return values. For a tool that modifies email state, more completeness would be expected to help an agent use it correctly.
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 schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, but it does provide context about the overall purpose which helps frame parameter usage. This meets the baseline expectation when schema coverage is complete.
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 specific action ('Reply to or forward an existing email') and resource ('email'), distinguishing it from sibling tools like 'email_send' (new emails) and 'emails_modify' (general modifications). It explicitly mentions continuing conversations, responding, and forwarding, which provides comprehensive purpose coverage.
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 provides clear context for when to use this tool ('to continue email conversations, respond to messages, or forward information to others'), but it doesn't explicitly state when NOT to use it or mention alternatives like 'email_send' for new emails. The guidance is helpful but lacks explicit exclusions or sibling tool comparisons.
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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