SolMail MCP
Server Quality Checklist
Latest release: v1.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: get_mail_quote for pricing, get_wallet_address for address retrieval, get_wallet_balance for balance checking, and send_mail for the core mailing action. There is no overlap or ambiguity between these functions, making tool selection straightforward for an agent.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern using snake_case: get_mail_quote, get_wallet_address, get_wallet_balance, and send_mail. The verbs 'get' and 'send' are appropriately applied, and there are no deviations or mixed conventions, ensuring predictable naming throughout.
Tool Count4/5With 4 tools, the count is reasonable for the server's purpose of handling physical mail via Solana. It covers essential operations like quoting, wallet management, and sending, though it might be slightly thin if advanced features like tracking or cancellation were expected. Overall, it's well-scoped but could benefit from minor additions.
Completeness4/5The tool set covers the core workflow: quoting, wallet setup, and sending mail. However, there are minor gaps, such as missing tools for tracking sent mail, canceling transactions, or managing mail templates, which could limit agent flexibility in more complex scenarios. The basics are well-covered, but the surface is not fully comprehensive.
Average 3.7/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 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
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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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool is 'useful for receiving funds,' which hints at a read-only operation, but doesn't explicitly state behavioral traits like whether it requires authentication, has rate limits, or returns a specific format. This leaves gaps in understanding how the tool behaves beyond its basic purpose.
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 highly concise and front-loaded: two short sentences that directly state the purpose and a practical use case. Every sentence earns its place without redundancy or unnecessary elaboration, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and a usage hint, but lacks details on behavioral aspects like authentication or return format, which could be important for an AI agent to invoke it correctly in a broader context.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is applied as it compensates adequately for the lack of parameters by focusing on the tool's purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the public address of the configured wallet.' It specifies the verb ('Get') and resource ('public address'), and distinguishes it from siblings like get_wallet_balance (which retrieves balance, not address). However, it doesn't explicitly differentiate from all siblings (e.g., get_mail_quote, send_mail), 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage context with 'Useful for receiving funds,' suggesting when this tool might be appropriate. However, it lacks explicit guidance on when to use it versus alternatives (e.g., get_wallet_balance for checking funds) or any exclusions, leaving room for ambiguity in tool selection.
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?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it returns price in USD and estimated SOL amount based on exchange rates, indicating it's a read-only, non-destructive operation. However, it doesn't mention potential errors, rate limits, or authentication needs, leaving gaps in behavioral context. This is adequate but not comprehensive.
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 front-loaded and concise, consisting of two sentences that directly state the tool's function and return values without unnecessary details. Every sentence adds value: the first defines the purpose, and the second specifies the output. There is zero waste, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is somewhat complete. It covers the purpose and return values but lacks details on error handling, prerequisites, or full behavioral context. Without an output schema, it should ideally explain return formats more, but it does mention price and SOL amount, which is a partial compensation. This results in a minimal viable score of 3.
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, with clear details for both parameters (country and color). The description adds no additional parameter semantics beyond what the schema provides, such as explaining usage scenarios or constraints. According to the rules, with high schema coverage (>80%), the baseline is 3, which is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a price quote for sending physical mail.' It specifies the verb ('Get') and resource ('price quote'), and distinguishes it from sibling tools like send_mail (which likely sends mail rather than quoting). However, it doesn't explicitly differentiate from other quote-related tools if any existed, keeping it at 4 instead of 5.
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 context by mentioning 'sending physical mail' and 'current exchange rates,' suggesting it's for pricing mail services. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., no mention of when to choose get_mail_quote over send_mail or other siblings). The context is implied but not detailed, scoring a 3.
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?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it's a write operation ('Send physical mail'), involves payment ('creates a Solana payment transaction'), and external processing ('submits to SolMail for printing and mailing'). However, it lacks details on costs, delivery times, error handling, or confirmation mechanisms that would be helpful for an agent.
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 appropriately sized (two sentences) and front-loaded with the core purpose. Every sentence earns its place by explaining the process and prerequisite. Minor improvement could come from slightly more structured phrasing, but it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (involving cryptocurrency, physical mail, and external services), no annotations, and no output schema, the description is moderately complete. It covers the high-level workflow and prerequisite but lacks details on costs, success/failure responses, or integration specifics that would help an agent fully understand the operation.
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%, so the schema fully documents all parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain content length limits, address validation, or mailOptions implications). Baseline 3 is appropriate when the schema does all the work.
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 specific action ('Send physical mail'), resource ('using Solana cryptocurrency'), and process ('composes a letter, creates a Solana payment transaction, and submits to SolMail for printing and mailing'). It distinguishes from sibling tools like get_mail_quote (which only quotes) and wallet-related tools by focusing on the complete sending operation.
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 states 'Requires wallet configuration,' providing clear context for when to use this tool (when wallet is set up). However, it doesn't specify when to use alternatives like get_mail_quote (for cost estimation before sending) or when not to use this tool (e.g., for digital communication).
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?
With no annotations provided, the description carries full burden. It discloses the configuration requirement, which is useful behavioral context. However, it doesn't mention potential errors (e.g., if wallet isn't configured), rate limits, or what 'current' means in terms of freshness.
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?
Two sentences with zero waste. The first sentence states the purpose, the second provides crucial context about prerequisites. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read operation with no parameters and no output schema, the description is reasonably complete. However, without annotations or output schema, it could benefit from mentioning the return format (e.g., numeric balance in SOL) and potential error conditions.
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 0 parameters with 100% schema coverage, so the baseline is 4. The description doesn't need to explain parameters, and it appropriately doesn't attempt to add parameter information.
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 specific action ('Get'), resource ('current SOL balance'), and target ('configured wallet'). It distinguishes from sibling tools like get_wallet_address (which returns address) and send_mail (different resource).
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 provides clear context about when to use ('Requires wallet configuration'), indicating a prerequisite. However, it doesn't explicitly state when NOT to use this tool or mention alternatives among siblings.
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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