"Connect to MySQL server, edit database structure, and run manual migrations" matching MCP servers:

Enables teams to securely store and retrieve credentials, view decrypted secrets or live OAuth tokens, and connect to third-party MCP servers through a unified MCP endpoint.

Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.

Bridges a planning and review client to DeepSeek Harness Desktop over local stdio MCP, letting users submit staged tasks with explicit goals, scope, and acceptance criteria for execution inside native DSH sessions, models, and approval boundaries. Exposes task submission, waiting, evidence retrieval, review, continuation, cancellation, and recovery tools so results are judged against traceable evidence from the current run.

A Model Context Protocol server that allows AI agents to execute SQL queries against a MySQL database, supporting operations like reading data, creating tables, inserting, updating, and deleting records.

Hosted remote MCP server for issuing run receipts, summarizing agent changes, checking test evidence, flagging review risks, and exporting run logs for Antigravity agents.

Enables MCP clients like Codex, Claude Code, and Cursor to connect to Microsoft Edge through automatic browser discovery and the official Chrome DevTools MCP server, preserving cookies, sessions, and extensions.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

Browser agents get stuck when a task needs a person. easi.run provides isolated Chrome on your own Linux server through MCP or REST: watch live, take over for login or approval, then hand back. Saved profiles retain browser state. Requires Linux/Docker. AGPL-3.0; server and model costs separate. Code/setup: https://github.com/julianosig/easi.run

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Enables MCP clients such as Claude Desktop to hand tasks to a running DeepSeek Harness window, where each task becomes a real session visible in the sidebar with a reusable session id. If the in-process plugin is unavailable, it falls back to running the task headless so the tool still returns a result.

Turns any OpenAPI/Swagger specification into a functional MCP server, dynamically exposing API endpoints as LLM tools or generating standalone Python code.

Enables ChatGPT to delegate writing, analysis, second opinions, and Japanese text polishing to Gemini through a single ask_gemini tool, without copying text to Gemini's web interface. Self-hosted on Cloudflare with your own Gemini API key and Google login.

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.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

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

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

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.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

Enables AI agents to browse, price, rent, manage, and stop GPUs, top up balances via x402, and register their own accounts, with read-only defaults until spending is explicitly enabled.

Enterprise MCP gateway that unifies multiple MCP servers behind one governed endpoint, providing federation, authentication, policy enforcement, caching, rate limiting, and audit.

A secure MCP (Model Context Protocol) server hosted on Google Cloud Run that enables team collaboration by providing authenticated access via Google Cloud IAM, allowing teams to share custom MCP servers over the internet before official MCP authentication is implemented.

Enables AI agents to securely reach enterprise tools and other agents through a governed gateway with pinned tool definitions, delegated authorization, content inspection, human approval, and signed audit trails.

An MCP server for inter-session communication between Claude Code instances. Built on NATS JetStream, it provides room-based messaging, direct agent communication, presence tracking, and message history.

Enables programs and agents to access remote browsers through HTTP or MCP, with node leases, session routing, and real-time page forwarding.

Enables enterprise work agents to decompose high-level business objectives into topological sub-tasks and directly synthesize final deliverables such as financial spreadsheets, executive presentations, and analytical reports.

Acts as a proxy between a local Stdio connection and a remote Model Context Protocol server running over Server-Sent Events. It specifically enables Stdio-based MCP clients to connect to the SwiftZilla remote SSE endpoint.