"How to create draft emails using Gmail's support agent class" matching MCP servers:

MCP server for AI-native L1 support: triages tickets, answers from a knowledge base, escalates to L2 via Telegram/GitHub, and manages feedback, with a LangGraph workflow and safety guardrails.

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Enables job-application lookup and domain support through MCP, exposing tools such as job lookup by ID over a local HTTP endpoint.

Enables local, deterministic management and search of point-of-sale support data—branches, terminals, incidents, and incident history—with read-only queries and mutating tools over stdio using simulated SQLite data.

Implements the Chain of Draft reasoning approach to generate minimalistic intermediate reasoning outputs while solving tasks, significantly reducing token usage while maintaining accuracy.

Enables enterprise SaaS support teams to get retrieval-augmented answers from indexed support documentation and to run natural-language questions as SQL queries against a support PostgreSQL database. It returns answers with source references and exposes the generated SQL alongside its results, with optional tracing and evaluation.

Enables semantic search, retrieval, and summarization of Gmail emails with privacy-aware classification and PII sanitization.

An AI-powered support ticket management system that lets users retrieve, search, and update support tickets using natural language.

Enables users to search for hotels by location and maximum price per night, returning hotel options with ratings and estimated total costs.

Enables read-only, user-initiated searches of public r/comfyui troubleshooting discussions, returning titles, excerpts, and direct Reddit links to help find existing solutions before posting duplicate support questions.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

AI agents can search and match Korean space, aerospace, and defense R\&D support program announcements. It provides MCP tools to filter by applicant type, deadline, and source family.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables Claude to translate natural-language business questions into safe, read-only SQL queries by exposing tools for listing tables, inspecting schemas, and executing row-capped SELECT statements against PostgreSQL.

An MCP-compatible server providing tools for retrieving order statuses, searching knowledge bases, and managing support tickets. It facilitates automated customer service interactions by exposing internal CRM and database functions through a JSON-RPC interface.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Enables natural-language Q&A over customer support ticket data. Provides tools for schema inspection, SQL-based ticket counts and grouping, and full-text search for customer wording without requiring API keys.

Enables lookup of licensed US real estate agents on official state license registers by license number or name, returning the brokerage of record along with its active agent count, size band, and the agent's license status and expiry. It also lists every active agent at a given brokerage or every brokerage office in a zip code across 19 states.

Enables AI assistants to research sponsorship contacts by searching and verifying professional emails through Monid, while saving missions, sources, and evidence locally.

Enables AI agents to search and inspect a Windows machine's local inventory of agents, skills, MCP servers, projects, and cross-agent work records, with tools for full-text search, overviews, project details, and reindexing. All data stays local and only matching snippets enter model context.