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Anthropic MCP Server

MCP Server

Post tweets from X using Google Sheets via Anthropic API

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Updated Jan 3, 2025

About

This MCP server streams data from a Google Sheet to the Twitter/X platform using Anthropic’s model for content generation and scheduling, enabling automated social media posting.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

The Anthropic MCP Server is a lightweight, purpose‑built Model Context Protocol (MCP) service that bridges the gap between AI assistants and social media automation. It enables Claude or any MCP‑compliant client to post tweets (or X updates) directly from a structured Google Sheet, turning a simple spreadsheet into an automated publishing engine. This eliminates the need for manual API handling or custom scripts, allowing developers and content teams to focus on strategy rather than plumbing.

Solving a Common Workflow Bottleneck

Content creators often maintain a backlog of posts in Google Sheets for scheduling, editorial approvals, or collaborative editing. Traditionally, moving that data to X required writing a dedicated script, managing OAuth tokens, and handling rate limits. The Anthropic MCP Server abstracts all of that complexity behind a single, well‑defined endpoint: the client sends a request with a row reference or a batch of rows, and the server takes care of authentication, payload formatting, and error handling. This streamlines workflows for marketing teams, PR agencies, or personal brands that rely on spreadsheets as their primary content repository.

Core Capabilities

  • Row‑to‑Tweet Mapping – Each spreadsheet row can contain a tweet body, media URLs, hashtags, or reply targets. The server translates these columns into the appropriate X API payload.
  • Batch Publishing – Multiple rows can be posted in a single request, respecting X’s rate limits and ensuring efficient throughput.
  • Error Reporting – If a tweet fails (e.g., due to content policy or duplicate text), the server returns detailed status codes and messages that can be logged or displayed in a dashboard.
  • Secure Credential Handling – OAuth tokens and API keys are stored server‑side, so clients never expose sensitive information. The MCP protocol handles token refresh transparently.
  • Extensible Resource Model – Developers can expose additional resources (e.g., fetching tweet analytics or scheduling future posts) by extending the MCP schema, keeping all interactions within a single protocol.

Real‑World Use Cases

  • Social Media Agencies – Automate bulk posting for multiple clients while keeping editorial control in a shared Google Sheet.
  • Event Management – Quickly push time‑sensitive updates or announcements by editing a row and triggering the MCP endpoint.
  • Personal Branding – Maintain a “draft” sheet of ideas that can be promoted to X with a single click, without exposing credentials.
  • Data‑Driven Campaigns – Generate tweets from analytic dashboards stored in Sheets, enabling real‑time reporting and engagement.

Integration with AI Workflows

Claude or other MCP clients can invoke the server as part of a larger content generation pipeline. For example, an AI assistant might draft tweet text in response to user prompts, write the result into a Google Sheet via another MCP endpoint, and then trigger the Anthropic MCP Server to publish it. This creates a seamless loop: generate → edit in sheet → publish, all orchestrated through MCP calls. The server’s predictable response format also allows AI agents to confirm success, handle retries, or prompt for corrections automatically.

Unique Advantages

Unlike generic Twitter bots that require manual setup, this MCP server offers a plug‑and‑play experience tailored for spreadsheet workflows. Its tight coupling with Google Sheets eliminates the need for additional data storage layers, reducing latency and simplifying maintenance. Moreover, by exposing publishing as a formal MCP resource, developers can integrate it into broader AI‑driven automation ecosystems—such as combining with language models for content ideation, analytics tools for performance tracking, or workflow engines for approval gates—without reinventing authentication or API handling logic.