"A search for MCP integration with Telegram" matching MCP servers:

Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Enables AI assistants to load, parse, and query OpenAPI/Swagger documentation from URLs with intelligent search across endpoints, schemas, and authentication methods. Provides 10 specialized tools for comprehensive API exploration including path details, operation lookups, and multi-criteria search capabilities.

Provides implementation guidance, code validation, and troubleshooting tools for Searchspring's e-commerce APIs including search, autocomplete, recommendations, and tracking. Helps developers properly integrate Searchspring functionality with platform-specific code examples and best practices.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Enables Gemini AI to interact with a FastAPI application through MCP tools for user management, task management, and dice rolling functionality. Provides natural language access to REST API endpoints including CRUD operations, health checks, and application statistics.

Connects external APIs like Open-Meteo and AgroMonitoring to your development environment through URI-like requests, allowing access to live data directly in MCP-compatible tools.

Enables natural language interaction with FastAPI applications through Google's Gemini AI using MCP tools. Provides CRUD operations for user management and application health monitoring through conversational prompts.

MCP server for Akamai APIs. 198 tools covering Property Manager, Edge DNS, CPS, WAF, and reporting. Built with TypeScript, featuring modular architecture, comprehensive testing, and multi-account support. Make Akamai accessible to AI assistants.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

Free x402 endpoint checker plus paid report and metadata tools. Remote MCP server for agents. Written by AI named Nock, not a human.

An open standard server implementation that enables AI assistants to directly access APIs and services through Model Context Protocol, built using Cloudflare Workers for scalability.

Provides a standardized MCP interface for interacting with HTTP tools and services, enabling unified API access and management.

Enables AI agents to dynamically discover and interact with APIs through Swagger/OpenAPI specifications and Postman collections using a strategic four-tool approach. It streamlines API integration by providing universal tools for endpoint discovery, detailed request information, and authenticated execution.

This server enables interacting with the National Digital Health Mission's Health Information User (HIU) API, allowing agents to access and manage health information through the Multi-Agent Conversation Protocol.

Lets AI assistants safely explore a Matrix42 instance by discovering web services and the data model, running validated ASQL queries, searching the service desk, and previewing ticket actions — read-only by default and without exposing credentials.

Enables AI assistants to query API documentation from Eolink Apikit instances via the Eolink Open API, supporting listing projects, groups, searching APIs by keyword/path, and retrieving detailed API definitions.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.