"How to get information about Telegram channels" matching MCP servers:

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Enables Claude to interact with Telegram channels and groups through API or web scraping for reading posts and searching.

Reads public Telegram channel pages and exposes them as MCP tools over Streamable HTTP/JSON-RPC, enabling retrieval of channel info, latest posts, and search without Telegram API credentials.

A containerized service that enables MCP clients to interact with data and perform actions through a remote browser environment. It supports live streaming of the container desktop and offers proxy configuration for location-based browser sessions.

Enables agents to search and retrieve job postings from Telegram's public job board through standardized MCP tools (search_jobs and get_job), with keyword, location, remote, and date filtering. It works read-only with any MCP host and returns normalized job details such as title, company, apply URL, and posting date.

An MCP server that automates converting diverse content sources like WeChat articles, YouTube videos, and various document formats into AI-generated outputs such as podcasts and slide decks via Google NotebookLM. It integrates specialized tools for web scraping, OCR, and file transformation to facilitate seamless content generation through natural language.

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Enables converting any webpage to clean LLM-ready markdown, with extraction, article, and news modes, using a real browser with anti-bot handling.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Scrapes the official Telegram Bot API documentation and provides tools for querying methods, types, fields, and relationships.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Converts X (Twitter) posts into JSON, PDF, PNG, Markdown, or Slack/Discord messages using public endpoints, no API key or login required.

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

Self-hosted MCP toolkit providing web search, Wikipedia, and arXiv access without mandatory API keys, delivered as a Docker Compose bundle.

Enables users to retrieve and structure shipment tracking information from DB Schenker's website using natural language queries.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Converts any webpage URL to clean, well-formed Markdown with title and H1 preservation, URL validation, and graceful fallbacks. One of 16 single-purpose servers in an open-source monorepo with full CI/CD to PyPI.