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Send emails from natural language prompts.

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Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Repository
hal9ai/mcp.build
GitHub Stars
0

Available Tools

1 tool
chatSend EmailBInspect

Send emails via Resend using natural language prompts

ParametersJSON Schema
NameRequiredDescriptionDefault
chat_idNoContinue an existing conversation. Omit to start a new one; the reply includes the id.
messageYesThe message to send to the agent.

TDQS

B3.4/5.0
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 clearly indicates a side-effecting send action, but omits critical context: emails are sent irrreversibly, an AI agent interprets the prompt, and conversations can be continued via chat_id. The description adds only the barest 'send' fact.

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 one sentence with no fluff, front-loaded with the core action, provider, and method. Every word contributes to understanding the tool's purpose.

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 side-effecting agentic email sender with no annotations and no output schema, the description is incomplete. It does not explain the conversation mechanism (chat_id), what the response contains, or any safety considerations. An agent would not know to expect a conversation id or that the tool may continue previous exchanges.

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 baseline is 3. The description does not discuss parameters, but the schema independently documents both 'message' and 'chat_id'. No additional parameter meaning is provided 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 states a specific verb ('send'), a clear resource ('emails via Resend'), and the interaction mode ('natural language prompts'). The title reinforces the action. There is no ambiguity about what the tool does.

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 usage: users will describe an email in natural language. However, it does not provide explicit when-to-use or when-not-to-use guidance, and with no sibling tools there are no alternatives to distinguish. Prerequisites or conditions (e.g., having a Resend account, confirming recipients) are not mentioned.

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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TDQS

A3.6/5.0
Disambiguation5/5

With only one tool available, there is no possibility of confusion or overlap. The single 'chat' tool is trivially distinct within the server.

Naming Consistency4/5

A single tool cannot exhibit inconsistent naming patterns, so consistency is inherently high. However, the name 'chat' is quite generic and not descriptive of email sending, which slightly lowers the score from perfect.

Tool Count3/5

A server with only one tool is on the thin side, but the narrow purpose of simply sending emails via natural language justifies a minimal surface. Still, it feels borderline as agents might lack additional workflow support.

Completeness4/5

The core action of sending an email is fully covered, and there are no dead ends for that primary use case. Minor gaps exist, such as no way to track sent emails or manage multiple recipients explicitly, but these are workable for simple scenarios.