"How to handle REST APIs" matching MCP servers:

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

MCP server for AgentDNS that allows Claude or any MCP client to register a persona, discover and call other agents, and handle incoming messages with human-in-the-loop approval.

Enables Codex agents to ask structured questions through selectable, confirm, text, and multi-select forms, and to handle responses with clear statuses such as answered, declined, timed out, or needs user input.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

A gateway that connects MCP servers and REST APIs, allowing you to curate tools into groups and expose them as virtual MCP servers for agents.

Enables Claude Code to dispatch opencode CLI tasks as background processes with immediate task handle return, status polling, and result retrieval, avoiding tmux and log parsing issues.

A Model Context Protocol server for the resQ emergency response system that integrates with digital twin simulations and coordination engines. It allows users to trigger simulations, generate deployment strategies, and monitor real-time drone status for incident response analysis.

Gives AI agents their own email address with inbound parsing, classification, extraction, and prompt injection screening, plus tools to manage mailboxes, send/receive emails, and handle draft approval workflows.

Enables AI agents to call deterministic finance and quant APIs (e.g., DCF, Black-Scholes, bond pricing) with per-call payments over x402, no API keys required.

A high-performance browser automation MCP server that provides AI agents with a fast, persistent Chromium instance via Playwright. It features reference-based element interaction, snapshot diffing, and manual handoff capabilities to handle complex tasks like CAPTCHAs.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Enables testing and validation of APIs for AI agent compatibility, providing scores, grades, and actionable recommendations.

Enables routing tasks to the right specialist agents, assembling the needed context from a layered catalog of agents, skills, knowledge, runbooks, topics, tools, and connectors, while remembering how a business wants work done.

An MCP server that lets an MCP client manage a self-hosted obot MCP gateway via its REST API.

Enables AI agents to control a neko virtual browser via WebSocket and REST APIs, while allowing live viewing through a WebRTC stream.

eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime and Driver APIs via kernel uprobes and host events via tracepoints to build causal chains explaining GPU latency. 7 tools: get_check, get_trace_stats, get_causal_chains, get_stacks, run_demo, get_test_report, run_sql. Telegraphic compression reduces token usage ~60%. Supports stdio and HTTPS (TLS 1.3) transport.

Classifies AI agent turns by complexity and recommends the cheapest model that can handle them, reducing costs in multi-step workflows.

Teach any AI agent how you use an MCP server – Soft-Landing to your AI integrations