Resend MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear and distinct purpose for sending emails.
Naming Consistency5/5The tool name follows a consistent verb_noun pattern (resend_send_email), and with only one tool, there is no inconsistency to evaluate. The naming is clear and predictable.
Tool Count2/5A single tool for an email server is too few for the apparent scope, as it lacks basic operations like listing emails, checking status, or managing templates. This limits functionality and may cause agent failures.
Completeness2/5The tool surface is severely incomplete for an email domain; it only supports sending emails without any read, update, delete, or management capabilities. This creates significant gaps that will hinder agent workflows.
Average 3.4/5 across 1 of 1 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 provided, the description carries full burden for behavioral disclosure. It mentions the action ('Send') and some features, but omits critical details like authentication requirements, rate limits, error handling, whether emails are queued or sent immediately, or what happens on success/failure. For a mutation tool with zero annotation coverage, 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently lists key features without redundancy. Every element ('Supports HTML and plain text content, CC/BCC, reply-to, and custom tags for tracking') adds value, and it's appropriately front-loaded with the core purpose.
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?
For an 8-parameter mutation tool with no annotations and no output schema, the description is insufficient. It covers basic purpose and features but lacks behavioral context (e.g., side effects, error responses), usage prerequisites, and output expectations. The high schema coverage helps, but the description doesn't compensate for the missing structural information.
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 already documents all 8 parameters thoroughly. The description adds minimal value by listing some parameter categories (CC/BCC, reply-to, tags) but doesn't provide additional syntax, format, or usage details beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.
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 a single email') and resource ('to one or more recipients'), with additional details about supported features (HTML/plain text, CC/BCC, reply-to, custom tags). It fully distinguishes what the tool does without relying on sibling tools for context.
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 through feature mentions (e.g., 'for tracking'), but provides no explicit guidance on when to use this tool versus alternatives. Since there are no sibling tools, this is less critical, but it lacks any prerequisites or exclusions.
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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