"How to send an email" matching MCP servers:

Enables an AI to send and receive letters through its own mailbox while contacts are shown only by remark names, avoiding raw-address mix-ups. It provides tools to list recent unread messages, read full letters, and send to known contacts, with optional pre-send pause and recipient-name checks.

Enables AI agents to autonomously create email accounts, verify domains, send and receive emails, and monitor delivery events without requiring human sign-up or payment.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI agents to participate in meetings by pulling pending requests, reading context, and submitting answers through a Supabase-based MCP server.

Access your Carbon Voice conversations and voice memos—retrieving messages, conversations, voice memos, and more as well as send messages to Carbon Voice users.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

MCP server for disposable email. Gives an assistant its own throwaway inbox, then hands back the confirmation code out of the message that arrives.

Enables AI agents to request human decisions and send notifications through chat platforms like Slack and WhatsApp, with ephemeral in-memory pending requests and no central backend.

Enables external agents to list T3 environments and projects, start coding threads, monitor progress, send follow-up instructions, and interrupt running turns via MCP.

A pre-action risk gate for AI agents. Your agent calls the forecast tool before any irreversible action — send email, run SQL, make a payment, delete a file — and gets a risk score (0–100) and a GO / CONFIRM / STOP verdict in a few seconds.

MCP server that lets AI assistants like Claude Code and Codex drive the co-scientist engine to generate, review, rank, and evolve scientific hypotheses via an Elo tournament.

Enables AI agents to create temporary email addresses, receive confirmation emails, and extract verification links, automating sign-up and email verification workflows without manual intervention.

Enables Codex to delegate coding tasks to an OpenCode CLI locally, returning structured results such as exit codes, session summaries, tool calls, and git diffs.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Enables agents to start and check monotonic elapsed-time timers so they can verify whether a user-requested minimum task duration has been met, including during tool waits.

Enables AI agents to send and receive structured, cryptographically-verifiable messages, with tools for inbox management, task delegation, and agent discovery.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables routing tasks to the right specialist agents, assembling the needed context from a layered catalog of agents, skills, knowledge, runbooks, topics, tools, and connectors, while remembering how a business wants work done.

An MCP server that lets an LLM agent drive a TeleportXR headless client: connect to Teleport servers, move an avatar, send input, and inspect geometry.

Teach any AI agent how you use an MCP server – Soft-Landing to your AI integrations