@ghostpaw/telegram

@ghostpaw/telegram

Telegram bot channel engine — fetch transport with zero runtime dependencies, SQLite message mirror with FTS5 full-text search, eager file BLOB storage, markdown rendering, and a structured LLM tool facade.

Every incoming update is mirrored into a local SQLite database before your handler runs, giving you a persistent, queryable record of everything the bot sees — including the raw bytes of every photo, document, voice message, and video, downloaded and stored immediately on receipt. It ships as a single prebundled blob designed for two audiences at once: human developers building bot backends in code, and LLM agents operating through a structured tool facade.

MCP server

Every client below starts the same stdio server: npx -y @ghostpaw/telegram mcp. Messages live in ~/.ghostpaw/telegram.db unless the GHOSTPAW_TELEGRAM_DB environment variable (absolute path) or --db <path> says otherwise.

Claude Code

claude mcp add ghostpaw-telegram -- npx -y @ghostpaw/telegram mcp

or as a plugin, which also installs the skill:

/plugin marketplace add GhostPawJS/telegram
/plugin install ghostpaw-telegram@ghostpaw-telegram

Codex CLI (~/.telegram/config.toml)

[mcp_servers.ghostpaw-telegram]
command = "npx"
args = ["-y", "@ghostpaw/telegram", "mcp"]

Cursor (.cursor/mcp.json), Claude Desktop (claude_desktop_config.json) or a project .mcp.json:

{
  "mcpServers": {
    "ghostpaw-telegram": {
      "command": "npx",
      "args": ["-y", "@ghostpaw/telegram", "mcp"]
    }
  }
}

Claude Desktop users can also install server.mcpb from the latest GitHub release. A Dockerfile is included for container hosts: docker build -t ghostpaw-telegram . && docker run -i --rm -v telegram:/data ghostpaw-telegram.

The server speaks MCP 2026-07-28 (stateless, server/discover) and the initialize-based revisions 2025-11-25, 2025-06-18, 2025-03-26 and 2024-11-05.

Set TELEGRAM_BOT_TOKEN in the server environment to execute send and moderation actions. Without a token, these tools return plans; local reads and tool discovery work offline. The .mcp.json token placeholder must be supplied by the client environment. The server reads the mirror populated by your library transport; it does not poll for updates.

CLI

npx -y @ghostpaw/telegram tools
npx -y @ghostpaw/telegram call tg_read '{"subcommand":"list_chats"}'
npx -y @ghostpaw/telegram --db :memory: call tg_send '{"subcommand":"send_message","chatId":123,"text":"Hello"}'

The send example returns a plan unless TELEGRAM_BOT_TOKEN is set.

Agent Skill

SKILL.md and skills/telegram/ ship in the package. Print the skill with npx -y @ghostpaw/telegram skill or copy skills/telegram/ into your skills folder.

Install

npm install @ghostpaw/telegram

Requires Node.js 24+ (uses the built-in node:sqlite module).

Quick Start

import { DatabaseSync } from 'node:sqlite';
import { createBot, initTelegramTables } from '@ghostpaw/telegram';

const db = new DatabaseSync('bot.db');
initTelegramTables(db);

const bot = createBot({
  token: process.env.TELEGRAM_TOKEN!,
  db,
  onMessage: async ({ message, user }) => {
    console.log(user?.firstName, message.text);
  },
});

await bot.start(); // long-polling

Webhook mode — pass a webhook config instead:

const bot = createBot({
  token: process.env.TELEGRAM_TOKEN!,
  db,
  webhook: { path: '/webhook', port: 8443, secretToken: process.env.TG_SECRET },
  onMessage: async ({ message, user }) => { /* ... */ },
});

await bot.start(); // listens on port 8443

What It Stores

Every update is mirrored into SQLite before your handler runs:

• Messages — text, media, edits, reply edges, albums, threads (FTS5 full-text index with Unicode diacritic folding)
• Users — first name, last name, username, language code
• Chats — title, type, member count, forum flag
• Members — status, permissions, admin title per chat
• Reactions — emoji per user per message, with per-emoji counts and event log
• Files — metadata + raw bytes stored as BLOB, SHA-256 deduplicated; downloaded eagerly on receipt (DEFAULTS.autoDownload is deprecated and unused; it does not change this behaviour)
• Callbacks — inline button presses with data and answered state
• Bot state — arbitrary key/value store and running statistics

All eight tables are created in one call: initTelegramTables(db).

Two Audiences

Human developers

Use the read, write, and network namespaces for direct-code access to every domain operation:

import { read, write, network } from '@ghostpaw/telegram';

// query the local mirror — no network calls
const chat = read.getChat(db, chatId);
const messages = read.listMessages(db, { chatId, limit: 50 });
const results = read.searchMessages(db, chatId, 'invoice');
const chain = read.replyChain(db, chatId, messageId);

// retrieve a stored file blob
const bytes = write.getFileBlob(db, fileId); // Buffer | null

// send text and media
await write.sendMessage(bot.client, chatId, 'Hello');
await write.sendPhoto(bot.client, chatId, fileId);
await write.sendDocument(bot.client, chatId, buffer, { caption: 'Report' });
await write.broadcast(bot.client, chatIds, 'Announcement');

// streaming — progressive in-place edits
const stream = write.createStream(bot.client, { chatId });
await stream.append('Thinking...');
await stream.replace('Done.');

See docs/HUMAN.md for the full human-facing guide with worked examples.

LLM agents

Use the tools, skills, and soul namespaces for a structured runtime surface:

import { tools, skills, soul } from '@ghostpaw/telegram';

// 4 JSON-schema tools with structured ToolResult responses
const allTools = tools.telegramTools;
const readTool = tools.getTelegramToolByName('tg_read');
const result = readTool?.handler(db, { subcommand: 'search_messages', chatId, query: 'invoice' });

// 6 workflow playbooks for common multi-step scenarios
const allSkills = skills.telegramSkills;

// Herald persona for system prompts
const prompt = soul.renderTelegramSoulPromptFoundation();

Every tool returns a discriminated result with outcome: 'success' | 'no_op' | 'error', structured data, and next-step hints. No thrown exceptions to parse.

See docs/LLM.md for the full AI-facing guide covering soul, tools, and skills.

Package Surface

Export	Role
initTelegramTables(db)	One-shot DDL — call once at startup
createBot(config)	Full bot composition with built-in fetch transport; polling or webhook
adaptBot(grammy)	Bridge a raw grammy Bot to the MockBot executor interface
read	Query the local SQLite mirror (no network)
write	Send messages, media, and actions; manage file BLOBs
keyboards	Build inline keyboards and callback buttons
network	Manage polling and update dispatch
render	Pure markdown and text transformation
tools	4 JSON-schema tools for LLM agents
skills	6 workflow playbooks for LLM agents
soul	Herald persona for system prompts
DEFAULTS	Tuneable runtime constants

Tools

Tools return plans by default; existing synchronous handlers perform no outbound actions. To execute send and moderation actions, create an async facade explicitly:

const facade = tools.createTelegramToolFacade({
  client: bot.client,
  execute: true,
  perChatPerSecond: 1,
  globalPerSecond: 30,
  maxRetries: 2,
});
const result = await facade.handler(db, 'tg_send', {
  subcommand: 'send_message', chatId: 123, text: 'Hello',
});

Omit execute to retain plan-only behavior. Execution reuses the outbound executors, returns the shared result shape with action data and sent message IDs where applicable, and masks bot tokens in errors. Capacity-one token buckets limit each API call per chat and globally; Telegram 429 retry_after responses pause retries, with two retries by default. Limits apply per facade instance; reuse one facade for callers sharing a bot. Partial execution can occur when a multi-call action fails (for example, kick bans then unbans).

Four tools shaped around operator intent:

Tool	What it does
tg_read	Query messages, chats, users, reactions, edit history, reply chains
tg_send	Send, edit, delete, forward, pin messages; set reactions; broadcast
tg_manage	Ban, unban, restrict, promote, kick users; query member status
tg_connect	Get bot stats, read bot state, list active chats

Each tool exports runtime metadata — name, description, JSON Schema, side-effect level, readOnly flag — so agent harnesses can wire them without reading docs.

Skills

Six workflow playbooks as markdown strings:

Skill	Workflow
manage-telegram-conversations	Read context, reply, pin, track threads and albums
moderate-chat-effectively	Detect violations, warn, restrict, ban with audit trail
handle-group-administration	Promote, demote, migrate, configure permissions
broadcast-to-audience	Compose, send, handle errors, retry failed chats
search-and-retrieve-messages	Full-text search, reply chains, edit history
stream-progressive-responses	Debounced streaming with overflow and error recovery

Documentation

Document	Audience
docs/HUMAN.md	Human developers using the read/write/network API
docs/LLM.md	Agent builders wiring tools, skills, and soul
docs/RECIPES.md	Advanced UI/UX patterns: streaming, approval flows, pagination
docs/README.md	Architecture overview: storage model, surfaces, invariants
docs/entities/	Per-entity manuals with exact public API listings

The package has zero runtime dependencies. It uses Node 24 global fetch for Bot API requests and an in-repo synchronous Markdown parser. grammy and marked are development dependencies used for compatibility tests.

createBot accepts optional api: { fetch, apiRoot } settings for an injected fetch implementation or a custom Bot API endpoint. The default endpoint is https://api.telegram.org.

adaptBot continues to accept grammy Bot instances. Calls without uploads use api.raw; file uploads use the built-in client, so grammy API transformers do not apply to uploads. Its optional second argument accepts { fetch, apiRoot }.

Development

npm install
npm test            # node:test runner
npm run typecheck   # tsc --noEmit
npm run lint        # biome check
npm run build       # ESM + CJS + declarations via tsup
npm run test:dist   # built artifact checks (after build)
npm run check:deps  # verify zero runtime dependencies

The repo is pinned to Node 24.14.0 via Volta. Use whichever version manager you prefer.

Support

If this package helps your project, consider sponsoring its maintenance:

Anonyfox • MIT License