"A platform or application for messaging and communication services" matching MCP servers:

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 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.

A REST API built with FastAPI that exposes endpoints via Model Context Protocol (MCP), allowing clients to interact with CRUD operations through MCP interfaces.

An LLM-driven API testing platform exposed over MCP, enabling declarative test definition and DAG-based execution.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Provides AI assistants with access to AegisX UI components, CRUD generator commands, development patterns, and API contract discovery tools. It enables developers to browse component documentation, build generation commands, and test authenticated API endpoints through the Model Context Protocol.

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

A read-only MCP server that exposes Automeli's public API documentation (v2 canonical, v1 frozen) to LLMs via fetch and cache over www.automeli.com artifacts. It enables listing, searching, and retrieving endpoints, OpenAPI specs, error explanations, code snippets, and end-to-end flow guides.

yop-mcp 是一个专为易宝支付开放平台(YOP)设计的 MCP (Model Context Protocol) Server，提供了一套完整的工具函数，帮助开发者通过AI助手（如Claude、Cursor等）更便捷地获取YOP平台的相关信息、生成密钥对、下载证书等操作。

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.

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.

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.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

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 agents to connect to any GraphQL endpoint, introspect schemas, and execute queries or mutations through auto-generated tools.

Enables MCP-capable agents to search the curated gold-402 directory of x402 services, probe any endpoint for valid 402 payment terms, and optionally purchase a human editorial verdict for a resource.

MCP server for integrating with Hilo, the WhatsApp messaging platform. It provides API contracts, verification tools, and a guided plan for agents to build the integration.

Enables AI assistants to search, analyze, and debug application API traffic captured by Tusk Drift, including HTTP requests, database queries, distributed traces, latency metrics, and error rates.

A stdio MCP server that audits other MCP servers over the live protocol. It connects to any MCP target (stdio or HTTP), lints every tool's schema for agent-usability, then actually calls the tools with deliberately broken inputs to see how the server handles them, and returns a 0–100 conformance score with a per-dimension breakdown rendered as Markdown.