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Let an LLM securely read and send Gmail through MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "DAVS Gmail MCP Server" yet — see the docs or source repo.
Using DAVS Gmail MCP Server, list the 10 most recent emails in my Gmail account and return the sender, subject, and time.
A structured list of recent emails for quickly reviewing the inbox.
Using DAVS Gmail MCP Server, send a follow-up email to [email protected] with the subject "Project Status Check" and a concise, professional body.
A drafted and sent email matching the requested subject and tone.
Inject this PDF into DAVS Gmail MCP Server as context, then draft a reply email based on its contents.
A reply draft that uses the PDF content as supporting context.
Office workers can use an LLM to list Gmail messages, access account profile information, and draft or send emails with less manual work. It fits everyday inbox review and reply tasks.
When a reply needs supporting PDF material, the tool can inject the PDF as context so the LLM drafts a more grounded email. This is useful for project updates, explanations, and proposal responses.
Developers can connect this MCP tool to MCP-compatible LLM workflows so the model can interact directly with a Gmail account. It is useful for building email assistants or office automation prototypes.
It lets an LLM interact with a Gmail account through MCP, including listing emails, sending emails, accessing profile information, and injecting PDFs as context. The description also mentions OAuth2 authentication and a Streamlit interface.
Based on the provided description, you need OAuth2 authentication to connect a Gmail account. For detailed setup or installation steps, see the source repository.
Its focus is not a standard manual email interface, but exposing Gmail actions to an LLM through MCP and allowing email tasks to use PDF context. The provided material does not specify whether it supports broader client features.
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