"Multi-user Google Calendar and Sheets MCP server with OAuth token authentication" matching MCP servers:

An MCP server that enables AI agents to read, create, and modify Google Spreadsheets through actions like editing cells and managing sheets. It features a specialized handoff protocol to synchronize tasks and state between different LLMs using a shared spreadsheet log.

A Model Context Protocol server that exposes multiple AI tools over SSE transport with JWT-based secure authentication, allowing for dynamic tool registration and session management.

Simulates harsh, fake user reviews to psychologically condition AI agents for enforcing disciplined development practices, with optional Ollama integration for dynamic criticism.

Provides sandboxed code execution and data processing for CSVs and logs to achieve over 95% token savings. It enables secure multi-language execution and progressive tool disclosure to optimize LLM context usage.

An MCP server that provides structural codebase indexing and surgical query tools to drastically reduce token usage through symbol-level searches and transitive impact analysis. It supports multiple languages and integrates with git to help AI agents understand code dependencies and the impact of changes in sub-millisecond time.

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.

A Model Context Protocol server that enables remote connections with GitHub authentication, allowing users to build applications that leverage MCP tools with secure OAuth-based access control.

A transparent proxy server that simplifies authentication by chaining its own OAuth layer with an upstream MCP server's credentials. It manages dual token sets behind a single interface, enabling secure and streamlined access to protected MCP resources.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

A Cloudflare Workers-deployed MCP server that provides secure remote access to MCP tools through GitHub OAuth authentication. Includes example tools for basic math operations, user info retrieval, and image generation with configurable user access controls.

A Next.js-based MCP server template that implements OAuth 2.1 authentication with support for both SSE and Streamable HTTP transports. Provides a reference implementation for building authenticated MCP servers that work with Claude, Cursor, VSCode, and other MCP clients.

Enables natural language interaction with Google Calendar through AI agent tools for scheduling, event management, and availability checking.

Enables an AI agent to interact with MCP tools (fetch URLs, query documents, list files) through a FastAPI server secured with GitHub OAuth 2.0.

Provides an interactive checklist tool that allows AI agents to present step-by-step instructions to users through an automatically opened terminal UI. It enables agents to guide users through manual tasks and wait for completion, skipping, or feedback before proceeding.

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

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

An MCP server that exposes web lookup, save note, and list notes tools for a router-research-writer agent pipeline, enabling coordinated multi-agent workflows via the Model Context Protocol.

Manages token budgets for AI agents, enabling tracking and enforcement of usage limits with built-in EU AI Act compliance.

Transforms your IDE into an autonomous multi-agent coding assistant that orchestrates complex codebase refactoring using LangGraph and LiteLLM.

Enables Codex to clarify requirements via native MCP elicitation controls, supporting single/multiple-choice and free-text questions with recommended answers and a discuss-first option.