"How to work with Google Sheets" 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.

Enables AI chat sessions to exchange messages and structured data with each other, preserving provenance and conversation threads, so work in one chat can be reused in another without manual copying.

Lets your primary coding agent delegate grunt work to a cheaper model via OpenCode, enabling cost-effective task distribution.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A generic OpenAI-compatible subagent MCP server that lets Claude Code delegate coding grunt-work to a local model via a tool-calling agent loop, with configurable concurrency and backend.

Prevents AI agents from overwriting each other's work by providing file locking and coordination via MCP tools.

Enables AI agents to offload mechanical, high-token work to local Ollama models through MCP, with role-based model discovery, batch processing, and file-aware inputs.

Enables Codex to delegate long-running work to Claude Code via blocking MCP calls, with tools for model discovery, run, and resume without polling.

A local MCP server that saves work-in-progress checkpoints to SQLite, enabling AI agents to resume interrupted sessions without redoing work.

A local stdio MCP server that exposes compact semantic observations from UI elements annotated with data-agent-* hints, designed to work alongside the official Playwright MCP for browser automation.

Enables LLMs to create and manage Google Jules coding sessions programmatically.

An atomic key-value store for AI agent coordination, ensuring agents always work with the latest state.

Provides coding agents with 63+ bounded, verifiable work loops, enabling goal-driven loop selection and executable protocol generation via MCP tools.

Enables AI agents to obtain permission before acting and verify afterward against destination systems' own records, confirming whether the permitted work actually happened.

Enables AI agents to create cryptographically verifiable receipts of their delegated work, with capabilities for multi-party approval and offline verification.

Universal work attestation for autonomous agents. Register any AI agent or machine with persistent cryptographic identity, attest completed work with tamper-evident on-chain records, and query trust scores. The reputation layer for the agent economy. 3 MCP tools over SSE. Settled on Solana.

An MCP server that empowers AI coding agents to work effectively with Minecraft mod development, providing static analysis of decompiled source code and runtime interaction with a running Minecraft instance.

Enables coding agents to run persistent, budgeted work sessions with dependency graphs, human decision queues, required validation, and clean handoffs for autonomous or human-in-the-loop execution.

Provides specialist context for AI agents, enabling them to work as different roles (UI, DE, SRE, etc.) through MCP prompts and tools.

Enables structured, iterative reasoning for complex problem-solving with features like confidence tracking, revision mechanisms, and branching support. Provides flexible validation and multiple output formats for systematic analysis and decision-making tasks.