Telegram MCP Server
This server acts as a Model Context Protocol (MCP) server for the Telegram Bot API, enabling comprehensive automated management of a Telegram channel through AI clients like ChatGPT, Claude Desktop, and automation platforms like Make.com.
Core capabilities:
Send content - text messages, photos, videos, and documents with HTML/Markdown formatting and captions
Create interactive content - polls and quizzes with customizable options and anonymity settings
Message management - edit existing messages, delete messages, and add emoji reactions
Channel information - retrieve channel details and statistics
Easy deployment - seamless integration on cloud platforms like Railway.com via MCP protocol
Provides comprehensive Telegram Bot API integration for managing channels, including sending messages with HTML/Markdown formatting, sharing photos with captions, creating interactive polls and quizzes, adding emoji reactions, editing and deleting messages, and retrieving channel information.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Telegram MCP Serversend a photo of a sunset to our channel with the caption 'Good evening everyone!'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Telegram MCP Server with Pexels & WordPress
Полнофункциональный MCP (Model Context Protocol) сервер для интеграции с Telegram каналами, Pexels API и WordPress.
🚀 Возможности
12 Telegram функций: отправка сообщений, фото, видео, документов, опросов, реакций, редактирование, удаление, закрепление сообщений
5 Pexels API функций: поиск фото и видео, кураторские подборки, популярные видео
40+ WordPress функций: полное управление постами, страницами, медиа, пользователями, категориями, тегами, комментариями
MCP протокол: полная поддержка JSON-RPC 2.0
HTTP API: поддержка как MCP, так и REST API
Railway деплой: готов к развертыванию в облаке
UTF-8 поддержка: корректная обработка русского текста
Related MCP server: Telegram Channel MCP Server
📋 Доступные инструменты
Telegram (12 инструментов)
send_message- Отправка текстовых сообщенийsend_photo- Отправка фотографийsend_video- Отправка видеоsend_document- Отправка документовsend_poll- Создание опросовsend_reaction- Отправка реакцийedit_message- Редактирование сообщенийdelete_message- Удаление сообщенийpin_message- Закрепление сообщенийunpin_message- Открепление сообщенийget_channel_info- Получение информации о каналеget_channel_stats- Получение статистики канала
Pexels API (5 инструментов)
pexels_search_photos- Поиск фотографий по запросуpexels_get_photo- Получение фото по IDpexels_curated_photos- Кураторские фотографииpexels_search_videos- Поиск видео по запросуpexels_popular_videos- Популярные видео
WordPress (40+ инструментов)
Посты (Posts)
wordpress_get_posts- Получение списка постовwordpress_get_post- Получение поста по IDwordpress_create_post- Создание нового постаwordpress_update_post- Обновление постаwordpress_delete_post- Удаление поста
Страницы (Pages)
wordpress_get_pages- Получение списка страницwordpress_get_page- Получение страницы по IDwordpress_create_page- Создание новой страницыwordpress_update_page- Обновление страницыwordpress_delete_page- Удаление страницы
Медиафайлы (Media)
wordpress_get_media- Получение списка медиафайловwordpress_get_media_item- Получение медиафайла по IDwordpress_upload_media- Загрузка медиафайлаwordpress_update_media- Обновление медиафайлаwordpress_delete_media- Удаление медиафайла
Категории (Categories)
wordpress_get_categories- Получение списка категорийwordpress_get_category- Получение категории по IDwordpress_create_category- Создание новой категорииwordpress_update_category- Обновление категорииwordpress_delete_category- Удаление категории
Теги (Tags)
wordpress_get_tags- Получение списка теговwordpress_get_tag- Получение тега по IDwordpress_create_tag- Создание нового тегаwordpress_update_tag- Обновление тегаwordpress_delete_tag- Удаление тега
Пользователи (Users)
wordpress_get_users- Получение списка пользователейwordpress_get_user- Получение пользователя по IDwordpress_create_user- Создание нового пользователяwordpress_update_user- Обновление пользователяwordpress_delete_user- Удаление пользователя
Комментарии (Comments)
wordpress_get_comments- Получение списка комментариевwordpress_get_comment- Получение комментария по IDwordpress_create_comment- Создание нового комментарияwordpress_update_comment- Обновление комментарияwordpress_delete_comment- Удаление комментария
Информация о сайте
wordpress_get_site_info- Получение информации о сайтеwordpress_get_settings- Получение настроек сайтаwordpress_search- Поиск по контентуwordpress_test_connection- Проверка соединения
🛠 Установка
npm install
npm run build🚀 Запуск
# Локальный запуск
npm start
# Разработка
npm run dev🌐 Деплой на Railway
Подключите GitHub репозиторий к Railway
Railway автоматически определит Node.js проект
Настройте переменные окружения:
TELEGRAM_BOT_TOKEN- токен Telegram ботаTELEGRAM_CHANNEL_ID- ID канала (например, @channel)PEXELS_API_KEY- API ключ Pexels (получить на https://www.pexels.com/api/)WORDPRESS_URL- URL вашего WordPress сайтаWORDPRESS_USERNAME- имя пользователя WordPressWORDPRESS_APPLICATION_PASSWORD- пароль приложения WordPress
📡 API Endpoints
GET /- Информация о сервереGET /health- Проверка здоровьяGET /tools/list- Список инструментов (MCP)POST /- MCP JSON-RPC 2.0 эндпоинт
🔧 Использование
MCP клиенты (ChatGPT, Claude Desktop)
URL: https://telegram-mcp-server-production.up.railway.appREST API
# Получить список инструментов
curl https://telegram-mcp-server-production.up.railway.app/tools/list
# Отправить сообщение
curl -X POST https://telegram-mcp-server-production.up.railway.app \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "send_message",
"arguments": {
"text": "Привет из MCP сервера!",
"parse_mode": "HTML"
}
},
"id": 1
}'📁 Структура проекта
├── src/
│ ├── simple-server.ts # Основной MCP сервер
│ └── index.ts # Альтернативная реализация
├── dist/ # Скомпилированный код
├── package.json # Зависимости и скрипты
├── Procfile # Конфигурация Railway
├── tsconfig.json # TypeScript конфигурация
└── README.md # Документация✅ Статус
Railway URL:
https://telegram-mcp-server-production.up.railway.appВерсия: v2.2.0
Статус: ✅ Работает
MCP совместимость: ✅ Полная
Telegram интеграция: ✅ Активна
Pexels API: ✅ Активна
WordPress интеграция: ✅ Активна
Всего инструментов: 56+ (12 Telegram + 5 Pexels + 40+ WordPress)
📖 Документация
WordPress Integration Guide - Полная документация по WordPress интеграции
Pexels API Guide - Полная документация по Pexels интеграции
Telegram Setup - Настройка Telegram бота
Troubleshooting - Решение проблем
🎯 Готов к использованию!
Сервер полностью настроен и готов к работе с ChatGPT, Claude Desktop и другими MCP клиентами.
Новые возможности v2.2.0:
🌐 Полная интеграция с WordPress REST API
📝 Управление постами, страницами, медиафайлами
👥 Управление пользователями, категориями, тегами
💬 Управление комментариями
🔍 Поиск по контенту WordPress
📤 Загрузка медиафайлов по URL
🔐 Аутентификация через Application Passwords
Возможности v2.1.0:
✨ Интеграция с Pexels API
🖼️ Поиск высококачественных фотографий
🎥 Поиск профессиональных видео
📸 Кураторские подборки
🔥 Популярные видео
Available Tools
7 toolsdelete_messageC
Delete a message from the channel
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | Yes | Message ID to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Delete' implies a destructive mutation, the description lacks details on permissions required, whether deletion is permanent or reversible, rate limits, or error conditions (e.g., invalid message ID). This leaves significant gaps for safe and effective use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste—it directly states the tool's function without unnecessary words. It's front-loaded and efficiently communicates the core action, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature (implied by 'Delete'), no annotations, and no output schema, the description is incomplete. It doesn't address critical aspects like success/error responses, side effects, or security considerations, which are essential for a mutation tool in a messaging context with sibling operations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'message_id' documented as 'Message ID to delete'. The description doesn't add any meaning beyond this, such as format examples or sourcing instructions. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and the resource ('a message from the channel'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings (like 'edit_message' or 'send_message'), which would require specifying what makes deletion distinct from other message operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing message ID), exclusions (e.g., cannot delete messages from other users), or comparisons to sibling tools (like 'edit_message' for modifications instead of deletion).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
edit_messageC
Edit an existing message
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | Yes | Message ID to edit | |
| parse_mode | No | Parse mode for new text | |
| text | Yes | New message text |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool edits a message, implying a mutation, but doesn't cover critical aspects like required permissions, whether edits are reversible, rate limits, or what happens if the message_id is invalid. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence ('Edit an existing message'), which is front-loaded and wastes no words. It directly states the tool's action without unnecessary elaboration, making it efficient for quick understanding, though this conciseness comes at the cost of detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with 3 parameters) and the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral traits, usage context, or output expectations, leaving significant gaps for the agent to navigate. For a tool that modifies data, more comprehensive guidance is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter semantics beyond what the input schema provides. Since schema description coverage is 100%, the schema already documents all parameters (message_id, parse_mode, text) with descriptions and enums. The description doesn't explain how these parameters interact (e.g., parse_mode applies to the new text) or provide additional context, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('edit') and resource ('an existing message'), which provides a basic understanding of the tool's function. However, it doesn't differentiate this tool from potential siblings like 'send_message' or 'delete_message' beyond the obvious verb difference, nor does it specify what aspects of the message can be edited (e.g., text, formatting). This makes the purpose somewhat vague but still identifiable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid message_id), exclusions (e.g., cannot edit messages after a certain time), or comparisons to siblings like 'send_message' for new messages or 'delete_message' for removal. This lack of context leaves the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_channel_infoB
Get information about the Telegram channel
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves information, implying it's a read-only operation, but doesn't specify any behavioral traits such as authentication requirements, rate limits, error conditions, or what happens if the channel doesn't exist. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it easy for an agent to parse quickly. Every word earns its place in conveying the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (zero parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects like authentication or error handling. Without annotations or an output schema, the description should ideally provide more context about what information is returned and under what conditions, but it doesn't, leaving gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics beyond what the schema provides. A baseline score of 4 is appropriate since there's nothing missing, but it's not a 5 because the description doesn't explicitly state that no parameters are required, which could be slightly helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('information about the Telegram channel'), making the purpose immediately understandable. It distinguishes itself from siblings like send_message or delete_message by focusing on retrieval rather than modification. However, it doesn't specify what type of information is retrieved (metadata, statistics, etc.), keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. While it's implied that this is for reading channel information rather than sending or editing content, there's no explicit mention of prerequisites, timing, or comparisons to other tools. This leaves the agent with minimal context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_messageC
Send a text message to the Telegram channel
| Name | Required | Description | Default |
|---|---|---|---|
| parse_mode | No | Parse mode (HTML, Markdown, or MarkdownV2) | |
| text | Yes | Message text to send |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'send' implies a write operation, it doesn't mention authentication requirements, rate limits, error conditions, or what happens on success (e.g., message ID returned). The description lacks crucial operational context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after sending (success response, error handling), doesn't mention authentication or permissions needed, and provides minimal context about the Telegram channel environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, but doesn't need to compensate for gaps either. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('send a text message') and target ('to the Telegram channel'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'send_photo' or 'send_poll' which also send messages but with different content types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'send_photo' for images or 'edit_message' for modifications. It mentions the channel context but doesn't specify prerequisites, limitations, or when other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_photoC
Send a photo to the Telegram channel
| Name | Required | Description | Default |
|---|---|---|---|
| caption | No | Photo caption | |
| parse_mode | No | Parse mode for caption | |
| photo | Yes | Photo URL or file path |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Send') but doesn't cover critical aspects like required permissions, rate limits, error conditions, or what happens on success (e.g., message ID returned). For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool (sending data) with no annotations and no output schema, the description is incomplete. It doesn't explain behavioral traits, error handling, or return values, which are crucial for safe and effective tool invocation in this context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond implying 'photo' is required (matching the schema's required field). This meets the baseline for high schema coverage without adding extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send') and resource ('a photo to the Telegram channel'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'send_message' or 'send_poll', which would require mentioning it's specifically for photos rather than text or other media types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'send_message' or other send_* siblings. It lacks context about prerequisites (e.g., channel access), exclusions, or comparative use cases, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_pollC
Create and send a poll to the Telegram channel
| Name | Required | Description | Default |
|---|---|---|---|
| is_anonymous | No | Whether the poll is anonymous | |
| options | Yes | Poll options (2-10 items) | |
| question | Yes | Poll question | |
| type | No | Poll type | regular |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Create and send' implies a write operation, it lacks details on permissions, rate limits, error handling, or what happens after sending (e.g., poll visibility). For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and resource without unnecessary words. Every part earns its place by directly stating the tool's function, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a mutation tool (creating and sending a poll) with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like authentication needs, side effects, or response format, leaving gaps that could hinder an agent's ability to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters (question, options, type, is_anonymous) with details like defaults and constraints. The description adds no additional parameter semantics beyond what's in the schema, resulting in a baseline score of 3 as the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create and send') and resource ('a poll to the Telegram channel'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like send_message or send_photo, which could also involve Telegram channel interactions, leaving some ambiguity about when to choose this specific tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., channel access), exclusions, or comparisons to siblings like send_message for non-poll content. Without such context, the agent must infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_reactionC
Send a reaction to a message
| Name | Required | Description | Default |
|---|---|---|---|
| emoji | Yes | Emoji to send as reaction | |
| message_id | Yes | Message ID to react to |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the action but doesn't disclose behavioral traits like required permissions, whether reactions are reversible, rate limits, or response format. For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a mutation tool with no annotations, no output schema, and siblings involving message operations, the description is incomplete. It lacks context on behavioral implications, error conditions, or integration with other tools, leaving significant gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('emoji' and 'message_id'). The description doesn't add meaning beyond what the schema provides, such as emoji format examples or message ID sourcing. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('send a reaction') and target resource ('to a message'), providing specific verb+resource pairing. However, it doesn't differentiate from sibling tools like 'send_message' or 'edit_message' which also involve message interactions, missing explicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With siblings like 'send_message' and 'edit_message' available, the description lacks context about appropriate use cases, prerequisites, or exclusions for sending reactions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool has a clearly distinct purpose targeting specific actions in the Telegram domain. For example, send_message, send_photo, and send_poll handle different content types, while delete_message, edit_message, and send_reaction operate on existing messages with unique functions. No tools appear to overlap or cause confusion.
All tool names follow a consistent verb_noun pattern using snake_case, such as delete_message, edit_message, and send_photo. This predictable naming convention makes it easy for agents to understand and select the appropriate tool without ambiguity.
With 7 tools, this server is well-scoped for managing a Telegram channel, covering essential operations like sending various content types, editing, deleting, and reacting to messages. Each tool earns its place without feeling excessive or insufficient for the domain.
The tool set provides strong coverage for core Telegram channel interactions, including sending, editing, deleting, and reacting to messages. A minor gap exists in operations like retrieving message history or handling other media types (e.g., videos or documents), but agents can work around this with the available tools.
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