AwrAIter — Telegram channels について
AwrAIter は、AwrAIter アカウントを通じて Telegram チャンネルを管理する人向けのリモート MCP サーバーです。Telegram のユーザーボットを使わず、分析、情報源に基づく投稿案、コンテンツ計画、予約投稿を扱います。
主な機能
- 01チャンネル統計とパフォーマンス分析の閲覧
- 02チャンネル投稿と接続済み情報源の検索
- 03チャンネル指針に沿った投稿案の作成と確認
- 04コンテンツ計画の作成と空き枠の検索
- 05投稿の予約、公開、キャンセル
- 06ブランド概要とチャンネルの学びの管理
活用シーン
- 01最近の投稿のリーチとエンゲージメントを確認
- 02収集済みのチャンネル情報源から投稿案を作成
- 03空き枠に合わせて今後の投稿を計画
- 04MCP クライアントからチャンネル投稿を予約
MCP 対応
リモートの Streamable HTTP MCP サーバーを通じて、アカウントで認可された Telegram チャンネル向けに 29 のツールを提供します。OAuth 2.1 または個人アクセストークンで接続し、トークンには読み取り専用とフルアクセスの範囲があります。
設定
リモートサーバーはインストール不要です。クライアントを選んで設定をコピーするか、ワンクリックで導入できます。
https://awraiter.ai/mcpclaude mcp add --transport http ai-awraiter-telegram https://awraiter.ai/mcp{"mcpServers":{"ai-awraiter-telegram":{"type":"http","url":"https://awraiter.ai/mcp"}}}Cursor で開く{"servers":{"ai-awraiter-telegram":{"type":"http","url":"https://awraiter.ai/mcp"}}}VS Code で開く{"mcpServers":{"ai-awraiter-telegram":{"type":"http","url":"https://awraiter.ai/mcp"}}}{"mcpServers":{"ai-awraiter-telegram":{"serverUrl":"https://awraiter.ai/mcp"}}}コマンドはターミナルで実行し、JSON は各クライアントの MCP 設定に貼り付けて再起動します。認可が必要なサーバーは初回接続時にログインを求めます。
ツール
README(原文)English
プロジェクトの README よりこの README の日本語訳はまだありません。以下は英語の原文です。日本語の紹介はページ上部をご覧ください。
AwrAIter MCP Server
A remote MCP server for the Telegram channels you administer: read analytics, draft posts from your own scraped sources, build content plans, schedule and publish — from inside ChatGPT, Claude, or any MCP-capable client.
Not a userbot. No phone number, no login code, no .session file. The server acts through your AwrAIter account and reaches only the channels of the team you authorize.
Русская версия · Connection guide · Tool reference · Team and invites · awraiter.ai
Server
| URL | https://awraiter.ai/mcp |
| Transport | Streamable HTTP |
| Authentication | OAuth 2.1 (PKCE, dynamic client registration) or a personal access token |
| Registry name | ai.awraiter/telegram |
| Availability | Every plan, including the free tier |
Quick start
You need an AwrAIter account (sign in with Telegram) and at least one connected channel.
Claude (web / desktop)
Settings → Connectors → Add custom connector, paste the URL, press Connect, and confirm access for the team you want.
https://awraiter.ai/mcp
Claude Code
claude mcp add --transport http awraiter https://awraiter.ai/mcp
Agent skill (Claude Code, Codex and other agents)
The AwrAiter_skills repository ships a skill with the full tool contract, authentication, the draft → check → preview → schedule workflow and the guardrails an agent should follow:
# Claude Code — as a plugin
claude plugin marketplace add MediaZione/AwrAiter_skills
claude plugin install awraiter@awraiter
# Codex and any other agent with skills
npx skills add MediaZione/AwrAiter_skills --skill awraiter
ChatGPT
AwrAiter is not in the ChatGPT plugin catalog yet — add it as your own MCP server: Settings → Security and login → Developer mode, then chatgpt.com/plugins → +, paste the URL, keep OAuth and press Connect. In a chat, pick it from the tools menu. The ChatGPT/Codex desktop form has no OAuth option; connect it with a token instead (see below).
Clients that take a JSON config
{
"mcpServers": {
"awraiter": {
"type": "http",
"url": "https://awraiter.ai/mcp"
}
}
}
Clients without OAuth (token auth)
Create a token in the panel under MCP connection — it is shown once, together with ready-to-paste snippets (Claude Code command, JSON config, cURL, Node.js) that already contain it — and send it as a header:
Authorization: Bearer YOUR_TOKEN
Step-by-step instructions for Claude, Claude Code, ChatGPT, Codex, Gemini CLI and Qwen Code are in docs/connect.md; ready-to-paste config files are in examples/.
Tools
29 tools. The ones that change something are marked ✍️ — everything else is read-only.
| Tool | What it does |
|---|---|
list_teams | Teams you belong to; marks the active one |
switch_team ✍️ | Switch the active team (membership is verified server-side) |
list_channels | Channels owned by the active team |
get_channel | One channel's profile: name, chat id, language, description |
get_channel_stats | Subscribers, reach, ER and dynamics over 1–90 days |
get_channel_insights | What works for this audience, scored against the channel's own 30-day median |
review_posts | How recent posts did against the channel's own posts at the same age: above, on par or below |
get_recent_posts | Most recent published posts, newest first |
search_channel_content | Semantic search over the channel's own posts and source material |
search_sources | Search the channel's bound sources |
draft_from_sources | Freshest scraped sources not yet used in a post |
deep_analyze ✍️ | Deep AI analysis of channel performance — the one tool that spends the team's AI credits |
check_uniqueness | Is this draft a near-duplicate of existing posts or a copy of a source? |
score_post | Data-grounded quality signal for a draft, specific to this channel |
preview_post | Exact message that would be sent — title, body, media, formatting |
create_post_from_text ✍️ | Save a ready-to-publish draft from text the assistant wrote, with photos, videos or music tracks by link |
schedule_post ✍️ | Publish a draft now, or schedule it for a given time |
cancel_scheduled_post ✍️ | Cancel a scheduled post by its plan id |
get_content_plan | The channel's plan configuration and its slots |
create_content_plan ✍️ | Create a content plan for a channel |
find_free_slot | Earliest slot in the plan with no post yet |
get_channel_memory | The channel's brand brief, banlist and learnings journal |
set_brand_brief ✍️ | Replace the channel's brand/tone guidance |
add_banlist_entry ✍️ | Add a forbidden word to the channel's banlist |
remove_banlist_entry ✍️ | Remove a word from the banlist |
add_channel_learning ✍️ | Record a hypothesis or a proven learning about what works in the channel |
remove_channel_learning ✍️ | Remove a journal entry |
set_assist_mode ✍️ | How much the assistant coaches you: quiet, normal or coach |
get_playbook | Step-by-step operator playbook for a workflow |
What each tool returns, and the exact scope it needs, is in docs/tools.md.
Authentication
OAuth 2.1 with PKCE and dynamic client registration; redirect URIs are restricted to HTTPS or HTTP loopback, authorization codes are single-use, and refresh tokens rotate. A token is bound to one user, one team and one scope.
Personal access tokens come in two scopes:
| Scope | Allows |
|---|---|
read | Read-only tools; every ✍️ tool is refused server-side |
full | Everything the account can do in the panel |
Tokens are listed, and can be revoked, in the panel under MCP connection.
Security model
| Userbot-style Telegram MCP servers | AwrAIter | |
|---|---|---|
| What you hand over | Phone number, login code, session file | An OAuth grant to your own account |
| What it can reach | Everything your account can — DMs, groups, private material | Only the channels of the team you authorized |
| How it publishes | As you | Through the panel's own service admin, with the same permission checks as the UI |
| If the token leaks | Your whole Telegram account | Revoke the token in the panel; nothing else is exposed |
Every write goes through the same channel-level access control as the panel, and rate limits apply per token. The full model, and how to report a vulnerability, are in SECURITY.md.
About AwrAIter
AwrAIter is a panel for people who run Telegram channels: weekly content plans, AI drafts in your channel's tone, scheduled publishing, and analytics for everything published — growth, reach, ER/ERR, per-post performance, channel comparison, export to XLSX or Google Sheets. One channel is free forever; paid plans start at €9/month. See awraiter.ai.
Support and legal
- Questions and issues: awraiter.ai/support
- Terms of Service · Privacy Policy
- Operated by Mediazione Italia S.r.l. Payments are handled by Stripe; we never see card numbers.
- Your channel content stays yours — we do not train models on it unless you explicitly opt in (off by default).
License
Documentation and examples in this repository are released under the MIT License. The AwrAIter service itself is proprietary.
コメント
AI アプリケーションが外部のツールやデータソースに統一的な方法で接続するためのオープンなプロトコルです。クライアントはモデルとの対話を担い、MCP サーバーはツール・リソース・プロンプトテンプレートを提供します。標準メッセージでやり取りするため、1 つのサーバーを複数のクライアントで再利用できます。