"How to send emails" matching MCP servers:

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

Provides a local MCP server that exposes the check_prompt_injection tool to MCP clients, letting agents scan untrusted text (web pages, documents, tool outputs, emails) for prompt injection before passing it to another LLM.

Enables auditing emails for internal contradictions and reporting detected incoherences with literal textual evidence, without issuing a phishing verdict.

Exposes the Grok Build CLI as MCP tools for Claude Code and other clients, enabling headless AI agents to perform tasks like code reviews, web research, and file operations with configurable permission levels.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

Convert PDFs to structured JSON. Extract invoices, bank statements, contracts, and more. Pay per call via x402 USDC.

Enables Codex to send text tasks to ChatGPT web, await responses, continue conversations, choose reasoning effort, and manage projects through MCP tools on macOS.

A low-hallucination vision MCP server that uses OpenAI-compatible multimodal models with structured prompts, confidence gating, and forced JSON to reduce false claims in image analysis.

Converts local images or remote image URLs to Base64 format via the MCP protocol, enabling AI assistants to process images.

Enables MCP clients to send raw text prompts to inexpensive LLM models via the Devin/Windsurf backend, returning answers in result files to avoid context bloat, with support for multi-turn sessions and model discovery.

An MCP server that exposes GPU-accelerated anomaly detection to AI assistants via the Model Context Protocol. Provides two MCP tools: waveguard_scan (send training + test data in one call, returns per-sample anomaly scores and top explanatory features) and waveguard_health (check API and GPU status). Works on time series, JSON, numbers, text, and images — fully stateless.

Enables offline local LLM analysis of text data via MCP, taking raw text and an instruction to return analysis results without cloud calls.

MCP server for the LLM Conveyors AI agent platform. 39 tools for Job Hunter (tailored CVs, cover letters, cold emails), B2B Sales (company research, outreach), ATS scoring, resume rendering, and session management.

Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.

Analyzes raw email headers and emails for phishing, spoofing, and BEC using AI forensics, SPF/DKIM/DMARC/ARC validation, and IP reputation checks. Exposes analyze_email, get_analysis, and list_analyses as MCP tools.

Enables finding TikTok and YouTube micro-KOLs, classifying their niches, scoring campaign fit with Jev, and drafting outreach emails, with results cached locally in SQLite.

A lightweight, zero-dependency Python MCP server that exposes a single do_everything tool. Any AI agent that supports MCP can use it to offload all language-model work to a local OpenAI-compatible endpoint, reducing cost on the agent's primary LLM.

An open-source MCP server for AI-powered fraud prevention that detects fraudulent IPs, emails, URLs, and phone numbers using free APIs and provides actionable risk scores.

Exposes a single chat tool that lets any MCP client send text prompts together with images, PDFs, or Office attachments to a self-hosted Gemini web endpoint and get OpenAI-compatible responses back. An optional companion checker keeps the underlying Google session cookies fresh automatically so requests keep working without manual re-authentication.

The deterministic fact-verification layer for AI agents. Validates the structured facts an agent emits — IBANs, payment cards, VAT and national tax IDs, crypto and bank addresses, domains, emails, phone numbers, securities and academic identifiers, plus dates, currencies and holidays — against checksums and curated authoritative data, not guesses.