"Automating HTTP API Wrapping into MCPT Tool" matching MCP servers:

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 AI agents to send HTTP requests to any endpoint with full control over methods, headers, query parameters, and request bodies.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Free DEX aggregator API that returns executable swap calldata across 46 EVM chains. No API key required. Single GET request returns ready-to-sign transactions for any token pair.

Enables users to analyze HTTP response headers of any URL for security and configuration, returning a 0-100 security score, HSTS/CSP and header checks, server detection, caching details, and recommendations. Supports pay-per-call access via x402 micropayments.

Mock HTTP server implementing MCP (Model Context Protocol) with streamable HTTP transport, health endpoint, and example tools like echo and time.

An HTTP-based Model Context Protocol server for RiotPlan that exposes comprehensive planning tools, resources, and prompts for AI agents. It enables full plan lifecycle management, including ideation, shaping, execution tracking, and retrospective generation.

Enables MCP clients to perform HTTP GET requests to arbitrary URLs and receive response details.

Provides agents with tools to score a page's AI readiness, check which AI crawlers robots.txt blocks, and assess passage citability—all performed locally.

Turns any OpenAPI spec into a single-tool MCP server where the model writes JavaScript against a typed api object in a QuickJS sandbox, so multi-step tasks run in one round trip and only the final result reaches context. Credentials, rate limiting, retries, write gating and audit logging stay on the host, outside the sandbox.

Enables AI agents to interact with the UOL Accounting REST API through MCP, supporting reads immediately and mutating operations with explicit confirmation, and is designed for deployment on Railway and use with Cursor.

First HTTP-native MCP server for Obsidian that solves stdio transport bugs, enabling AI assistants to manage Obsidian notes without crashes.

MCP proxy server with semantic tool search for LLM coding agents. It reduces context window usage by activating only relevant tools based on user queries.

Enables lightweight web search discovery and on-demand extraction of cleaned page text from supplied URLs, returning snippets, headings, links, and saved full text for longer pages.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

MCP server for Wiki.js that exposes 29 tools for managing pages, comments, tags, assets, users, navigation, and more via HTTP/SSE with built-in mutation safety.

An MCP server implementation of Anthropic's Think Tool prompt engineering technique that enables Claude to break down complex problems and enhance its reasoning capabilities by providing a simple tool that echoes back thoughts.

Enables local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.

SSH automation MCP server that enables Claude and ChatGPT to execute commands, manage files, install packages, and control services on remote servers over SSH — supporting password, key, and agent authentication.

A stdio MCP server that gives clients DeepSeek-backed web search and page fetching capabilities. It supports multi-query searching with result counts and pacing options, plus retrieving fetched pages as capped Markdown output.

A single MCP server that provides dynamic access to thousands of APIs through discovery and proxy, eliminating the need to install and configure multiple separate MCP servers.

MCP server connecting Claude/Cursor to Codex CLI, enabling code analysis via @ file references, multi-turn conversations, sandboxed edits, and structured change mode.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

Enables AI assistants to interact with Gitea repositories through intelligent tools for issue/PR management, workflow analysis, compliance checking, and content generation, plus 200+ CLI commands for complete CRUD operations.

Enables to query real-time weather information for any city worldwide by automatically geocoding city names and retrieving temperature, precipitation, and other data via Open-Meteo APIs, seamlessly integrated with Claude Desktop.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

This is a powerful Model Context Protocol (MCP) server that integrates multiple AI coding agents—Anthropic Claude Code, OpenAI Codex, and Google Gemini—directly into your workflow. It enables seamless cross-provider analysis, leveraging Gemini's massive token window, Codex's specialized coding capabilities, and Claude's advanced reasoning.

MCP server that integrates Google Gemini CLI with AI assistants, enabling large file analysis and natural language queries without an API key.

A Model Context Protocol server that enables AI assistants to interact with Google Gemini CLI, allowing them to leverage Gemini's large token window for analyzing files and codebases using natural language commands.

Enables on-demand generation of TypeScript tools using an LLM with human-in-the-loop approval and safe sandboxed execution. It allows users to create and persist custom functionality through natural language requests.

A Model Context Protocol server exposing 58 online tools (crypto, data, image, text, etc.) and workflow execution, enabling MCP clients like Claude Desktop to invoke them via natural language.

A powerful Model Context Protocol (MCP) tool for exploring and managing different types of databases including PostgreSQL, MySQL, and Firestore.

Amazon MCP server and Amazon product data API for AI agents. Lets Claude, Cursor, ChatGPT and other MCP clients search Amazon, get real-time prices, reviews, product details, sellers, deals and best seller ranks, or look up any ASIN. One API key, 100 free requests a month.

Enables AI assistants to interact with multiple AI models through the OpenCode CLI with a unified interface. Supports plan mode for structured analysis, flexible model selection, and natural language queries with file references.

A reference implementation for creating an MCP server supporting Streamable HTTP & SSE Transports with OAuth authorization, allowing developers to build OAuth-authorized MCP servers with minimal configuration.

Publishes a stateless MCP endpoint on a Next.js App Router route that speaks Streamable HTTP and runs on any serverless host, exposing example tools (add, get_time, whoami) that clients like Claude Code, Cursor, and MCP Inspector can call. A loopback client forwards per-request context, such as a caller id or a user-supplied API key, in a header so tools can act for that one request without storing anything.

Exposes any stdio-based MCP server over the MCP Streamable HTTP transport so remote clients can reach it, spawning an isolated child process per session and gating access behind a secret URL path.

Provides an HTTP wrapper around the FIO Bank MCP server, enabling secure access to FIO Bank account data over HTTPS for Cursor and Railway via MCP Streamable HTTP with Bearer authentication.

Provides a 'reflect' tool that creates cognitive checkpoints for AI assistants, forcing structured step-by-step reasoning through complex problems to improve accuracy and maintain context during task execution.