"author:askeleven" matching MCP servers:

Enables agents to verify an email list before sending, returning a pass/fail plus keep, remove, and review categories with reasons. It exposes check_emails and check_file tools over stdio, with optional Analyzemail mailbox verification.

Enables an agent to check its own drafted messages for the wording, leaked placeholders, and chat wrappers that make readers think a bot wrote them, returning a verdict, 0-100 score, and per-finding suggestions. It also applies the safe fixes that need no judgement and reports what still requires a human or model rewrite before anything is sent.

Enables AI agents to ask, before sending each message, whether disclosure laws require them to admit they are an AI, returning the rules in force with citations and suggested wording. It also grades recorded conversations against 47 US, EU, UK, Canadian, and Australian disclosure rules.

Enables agents to validate a text message before sending it, checking segment count and encoding, recipient local send time, and opt-out wording, and to split an over-long message into ordered parts that each fit. It exposes check_sms and split_sms over stdio, returning a verdict, coded reasons, and the facts needed to send, schedule, or escalate to a person.

Checks a message thread before an agent replies, returning a keep/review/fail verdict with the reasons behind it so replies to autoresponders, bounces, or other bots are stopped. Also classifies single messages and, with a ledger, records sent and received messages across channels and threads to catch loops that span conversations.

Enables agents to scan incoming emails, web pages and messages for instructions aimed at the AI, wrap that untrusted content in a nonce-bounded fence the content cannot forge, and expose a check_action tool so the model's tool calls can be blocked or confirmed after it reads something from outside. It runs locally over stdio with zero dependencies and no network access.