GhostPaw Telegram

io.github.GhostPawJS由 GitHub 账号 GhostPawJS 发布v0.7.8更新于 Oct 29, 2026

Telegram message mirror, search, sending, and moderation tools.

已验证STDIO仅桌面数据库沟通与协作

概览

AI 生成的概览

本地 stdio MCP 服务器,让助手检索 Telegram 机器人聊天与消息的 SQLite 镜像,并规划或执行发送与群管理操作。

可以做什么
  • 检索与读取镜像数据:消息全文搜索、聊天、用户、成员、表情回应、编辑历史与回复链
  • 发送、编辑、删除、转发、置顶消息,设置回应与群发;未配置令牌时仅返回计划
  • 管理群组:封禁、解封、限制、提升、踢出成员并查询成员状态
  • 查看机器人统计、键值状态与活跃聊天列表
  • 附带六份工作流指南,涵盖会话管理、审核、群管理、群发、消息检索与流式回复
适用场景
适合通过该包的库传输运行 Telegram 机器人,并希望助手查询机器人所见内容,或在聊天客户端中起草、并在有令牌时执行发送与群管理操作的场景。
运行要求
以本地进程运行(npm 包 @ghostpaw/telegram,需 Node 24+ 以使用 node:sqlite,或使用发布版二进制)。SQLite 镜像须已由库传输写入,服务器本身不轮询更新。执行发送与群管理需要 TELEGRAM_BOT_TOKEN。数据库路径默认为 ~/.ghostpaw/telegram.db,可用 GHOSTPAW_TELEGRAM_DB 或 --db 覆盖。
安装前请注意
镜像包含私聊内容与原始文件数据,数据库文件属敏感信息。设置 TELEGRAM_BOT_TOKEN 后,工具可在真实聊天中发送、编辑、删除、转发、置顶、封禁、限制、提升与踢出,多步操作失败时可能出现部分执行。启用 GHOSTPAW_TELEGRAM_ALLOW_PRIVATE_URLS 会允许从本地与私有地址抓取媒体。

安装

在 SourceWeft 中

  1. 打开 控制台中的 GhostPaw Telegram,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

[GhostPaw telegram: Your bot remembers the chat, including what was edited.]

@ghostpaw/telegram

[npm] [CI] [site] [runtime deps] [MCP Registry] [node] [license]

Agent Telegram bots: every update mirrored into SQLite before your handler runs.

bash
ghostpaw-telegram --help             # after installing the release binary

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, which are downloaded in the background after the update is stored and kept once per SHA-256 hash. A failed download leaves the file row without a checksum, so you can retry it with write.downloadFile. 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: ghostpaw-telegram mcp. For npm-based environments, use 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

bash
claude mcp add ghostpaw-telegram -- ghostpaw-telegram mcp

or as a plugin, which also installs the skill:

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

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

toml
[mcp_servers.ghostpaw-telegram]command = "ghostpaw-telegram"args = ["mcp"]

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

json
{  "mcpServers": {    "ghostpaw-telegram": {      "command": "ghostpaw-telegram",      "args": ["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.

Noun-verb CLI

The 27 command paths derive from the 4 tool schemas:

text
bot stats | state <key> | chatsmirror message <chatId> <messageId>mirror messages <chatId> | search <chatId> <query>mirror chat <chatId> | chats | user <userId> | usersmirror reactions <chatId> <messageId>mirror replies <chatId> <messageId> | edits <chatId> <messageId>message send <chatId> <text> | edit <chatId> <messageId> <text>message delete <chatId> <messageId> | pin <chatId> <messageId> | unpin <chatId> <messageId>message typing <chatId> | forward <fromChatId> <messageId> <toChatId>member ban <chatId> <userId> | unban <chatId> <userId> | restrict <chatId> <userId>member promote <chatId> <userId> | kick <chatId> <userId> | show <chatId> <userId>member list <chatId>

Use help <noun> or <noun> <verb> --help for schema flags. Fields accept kebab-case flags, such as --can-send-messages true and --is-admin false. Objects accept JSON; arrays accept repeated flags or JSON. Values are literal, including a leading @; no flag reads a file. A single - reads stdin JSON; explicit flags override stdin fields. -- ends option parsing.

Global flags: --db <path>, --json, --quiet, --compact, --help/-h, --version/-V/-v, --no-color. Piped output defaults to JSON; --quiet suppresses stdout. completions bash|zsh|fish prints completion setup and version prints the package version and installation variant.

New command exit codeMeaning
0Success or no-op
1Tool error
2Usage or schema error
3Clarification needed or not found
4Conflict or version mismatch
70Unexpected internal error

Existing tools [--json], describe <tool>, call <tool> [JSON|-], flat tg_<tool> --parameter value, mcp and skill forms keep their behavior. The noun-verb send and moderation commands always return plans, including when TELEGRAM_BOT_TOKEN is set. Execution remains available through createTelegramToolFacade({ client, execute: true }); the existing tool-level CLI and MCP forms execute when TELEGRAM_BOT_TOKEN is set. Local mirror reads and plans work offline without credentials. GHOSTPAW_TELEGRAM_DB sets the default database, otherwise ~/.ghostpaw/telegram.db is used; --db overrides both.

Offline examples:

sh
ghostpaw-telegram mirror chats --db /tmp/telegram-port-example.db --jsonghostpaw-telegram message send 123 'Offline plan' --db /tmp/telegram-port-example.db --jsonghostpaw-telegram mirror messages 123 --db /tmp/telegram-port-example.db --json

The empty mirror returns no chats or messages. The send returns an action descriptor without sending a Telegram message.

CLI

bash
ghostpaw-telegram toolsghostpaw-telegram call tg_read '{"subcommand":"list_chats"}'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.

Use ghostpaw-telegram skill --short for the compact CLI cheat sheet, ghostpaw-telegram skill --list to list guides, and ghostpaw-telegram skill <guide> to read one.

On POSIX, CLI and MCP mirror databases are created with mode 0600, including new SQLite WAL/SHM files. Directories created for the database use mode 0700. Existing database and directory permissions are preserved. The mirror may contain private chat content and file blobs.

Agent Skill

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

Install

Release binary (default)

Each line downloads the latest release asset, checks it against the release's SHA256SUMS and installs it on the PATH (~/.local/bin on Linux/macOS; the Windows script adds its folder to the user PATH).

These lines never edit ~/.profile or other shell startup files: export PATH applies to the current shell only. To keep it in new shells, use the ~/.profile line below.

linux-x64:

sh
curl -fsSL https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.sh | sh -s -- --target linux-x64 && export PATH="$HOME/.local/bin:$PATH"

linux-arm64:

sh
curl -fsSL https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.sh | sh -s -- --target linux-arm64 && export PATH="$HOME/.local/bin:$PATH"

darwin-arm64:

sh
curl -fsSL https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.sh | sh -s -- --target darwin-arm64 && export PATH="$HOME/.local/bin:$PATH"

darwin-x64:

sh
curl -fsSL https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.sh | sh -s -- --target darwin-x64 && export PATH="$HOME/.local/bin:$PATH"

windows-x64 (PowerShell; persistently adds the install folder to the user PATH):

powershell
irm https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.ps1 | iex

To skip the persistent user PATH edit:

powershell
$env:GHOSTPAW_NO_MODIFY_PATH=1; irm https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.ps1 | iex

Pinned to a release:

sh
curl -fsSL https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.sh | sh -s -- --target linux-x64 --version 0.7.8 && export PATH="$HOME/.local/bin:$PATH"

Also adding ~/.local/bin to ~/.profile (edits ~/.profile once; skipped if it already mentions ~/.local/bin; zsh login shells read ~/.zprofile instead, so use that file name there):

sh
curl -fsSL https://raw.githubusercontent.com/GhostPawJS/telegram/main/install.sh | sh -s -- --target linux-x64 && { grep -qs '.local/bin' ~/.profile || echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.profile; } && export PATH="$HOME/.local/bin:$PATH"
text
$ ghostpaw-telegram --versiontelegram 0.7.8 (binary, linux-x64)

Scripts that compare versions should use --version --short or --version --json.

A session with the 0.7.1 linux-x64 binary against a fresh database, with no token set, so outbound commands only return the planned action and nothing is sent (output piped through jq to keep it short):

[ghostpaw-telegram 0.7.1 without a token: version, mirror chats, planned message send, typing and forward, account stats, account state and the tool list]

The same session as an animated GIF.

Other release installers:

sh
mise use -g github:GhostPawJS/telegramubi --project GhostPawJS/telegram --exe ghostpaw-telegram --in ~/.local/bineget GhostPawJS/telegram

For aqua, define a github_release package in aqua.yaml:

yaml
registries:  - name: telegram    type: local    path: telegram-registry.yamlpackages:  - name: GhostPawJS/telegram@v<VERSION>    registry: telegram

telegram-registry.yaml:

yaml
packages:  - type: github_release    repo_owner: GhostPawJS    repo_name: telegram    asset: ghostpaw-telegram-{{trimV .Version}}-{{.OS}}-{{.Arch}}.tar.gz    format: tar.gz    replacements: { amd64: x64 }    overrides:      - goos: windows        asset: ghostpaw-telegram-{{trimV .Version}}-windows-{{.Arch}}.zip        format: zip    files:      - name: ghostpaw-telegram

Install scripts verify SHA256SUMS. To verify a downloaded archive's build attestation:

sh
gh attestation verify <archive> -R GhostPawJS/telegram

Set GHOSTPAW_VERIFY=attestation for attestation verification in install.sh. Binaries are unsigned; macOS binaries carry an ad-hoc signature. For a browser download on macOS, remove quarantine with xattr -d com.apple.quarantine /path/to/ghostpaw-telegram. Linux binaries require glibc 2.28+; use npx on Alpine. See the binary build workflow.

Sizes for 0.7.1 (Node 26.12.1 inside each binary):

TargetArchiveBinary
linux-x6441.6 MB tar.gz117.4 MB
linux-arm6441.1 MB tar.gz115.1 MB
darwin-arm6444.8 MB tar.gz146.6 MB
darwin-x6446.3 MB tar.gz149.5 MB
windows-x6438.4 MB zip105.6 MB

Release installation is checked on ubuntu-24.04, macos-15 and windows-2025.

npx / npm (for npm-based environments)

sh
npx @ghostpaw/telegram --helpnpm install -g @ghostpaw/telegram

Requires Node 24+ for the built-in node:sqlite module. The npm package is 816 KB unpacked.

Library (for harnesses embedding it in code)

sh
npm install @ghostpaw/telegram
ts
import { tools } from '@ghostpaw/telegram';

See library usage.

Quick Start

ts
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:

ts
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

Docs

Read the manual for usage guides, recipes, architecture and entity references.

  • Overview: what the manual covers and where to start
  • Human usage: using the library directly in code
  • LLM usage: tools, skills and the soul prompt for agents
  • Recipes: patterns for menus, keyboards and replies
  • Architecture: how the code is laid out
  • Chats: every conversation the bot has seen
  • Messages: inbound and outbound messages
  • Users: bot and human accounts
  • Members: who is in which chat, with status
  • Callbacks: inline keyboard button presses
  • Files: photos, documents and voice notes
  • Reactions: emoji reactions and their counts

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 in the background for every incoming file (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:

ts
import { read, write, network } from '@ghostpaw/telegram';
// query the local mirror — no network callsconst 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 blobconst bytes = write.getFileBlob(db, fileId); // Buffer | null
// send text and mediaawait 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 editsconst 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:

ts
import { tools, skills, soul } from '@ghostpaw/telegram';
// 4 JSON-schema tools with structured ToolResult responsesconst 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 scenariosconst allSkills = skills.telegramSkills;
// Herald persona for system promptsconst 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

ExportRole
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
readQuery the local SQLite mirror (no network)
writeSend messages, media, and actions; manage file BLOBs
keyboardsBuild inline keyboards and callback buttons
networkManage polling and update dispatch
renderPure markdown and text transformation
tools4 JSON-schema tools for LLM agents
skills6 workflow playbooks for LLM agents
soulHerald persona for system prompts
DEFAULTSTuneable 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:

ts
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:

ToolWhat it does
tg_readQuery messages, chats, users, reactions, edit history, reply chains
tg_sendSend, edit, delete, forward, pin messages; set reactions; broadcast
tg_manageBan, unban, restrict, promote, kick users; query member status
tg_connectGet 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:

SkillWorkflow
manage-telegram-conversationsRead context, reply, pin, track threads and albums
moderate-chat-effectivelyDetect violations, warn, restrict, ban with audit trail
handle-group-administrationPromote, demote, migrate, configure permissions
broadcast-to-audienceCompose, send, handle errors, retry failed chats
search-and-retrieve-messagesFull-text search, reply chains, edit history
stream-progressive-responsesDebounced streaming with overflow and error recovery

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 }.

Remote media URLs

Media sends accept { url: 'https://example.com/image.jpg' }. Downloads use Node HTTP/HTTPS directly, independently of the Bot API fetch option. Only HTTP and HTTPS are supported. Every DNS result and redirect target is checked; private, local, link-local, multicast and reserved targets are blocked. Connections use a validated address to prevent DNS rebinding.

Downloads default to 50 MiB, a 30 second overall timeout (including DNS and redirects), and at most five redirects. Oversized bodies and non-2xx final responses fail with TELEGRAM_FILE errors.

Set api: { allowPrivateMediaUrls: true } in createBot, or set GHOSTPAW_TELEGRAM_ALLOW_PRIVATE_URLS=1, to permit private targets. Either opt-in permits access to local services and metadata endpoints; use it only with trusted media URLs. Client options mediaMaxBytes and mediaTimeoutMs override the size and timeout limits, for example:

ts
const bot = createBot({ token, db, api: { mediaMaxBytes: 10 * 1024 * 1024, mediaTimeoutMs: 15_000 } });

Development

bash
npm installnpm test            # node:test runnernpm run typecheck   # tsc --noEmitnpm run lint        # biome checknpm run build       # ESM + CJS + declarations via tsupnpm 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:

[GitHub Sponsors]


Anonyfox • MIT License

来源:README.md,提交 2e0bddc

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

2
  1. v0.7.8最新Oct 29, 2026
  2. v0.6.2Oct 25, 2026

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