🐦 X-Post MCP 🚀

Created By
subhadeeproy3902a year ago
A Model Context Protocol (MCP) server that allows interaction with the X API, along with a client to interact with the server using Google's Gemini AI.
Overview

What is X-Post MCP?

X-Post MCP is a client-server application that allows AI models to create and publish posts on X (formerly Twitter) using the Model Context Protocol (MCP). It provides a standardized interface for seamless integration between AI models and the X platform.

How to use X-Post MCP?

To use X-Post MCP, set up the server and client by following the installation instructions, obtain the necessary API credentials, and start the server and client. You can then interact with the AI model through an interactive chat interface to post to X.

Key features of X-Post MCP?

  • Seamless integration with the X (Twitter) API
  • AI-powered post creation using Google's Gemini models
  • MCP server exposing X posting functionality as a tool
  • Interactive chat interface for testing and demonstration
  • Secure handling of API credentials
  • Automatic truncation of posts exceeding X's character limit

Use cases of X-Post MCP?

  1. Automating social media posts using AI-generated content.
  2. Enhancing user engagement on X by posting timely updates.
  3. Testing and demonstrating AI capabilities in generating social media content.

FAQ from X-Post MCP?

  • Can I use X-Post MCP without an X Developer account?

No, you need to create a developer account and obtain API credentials to use X-Post MCP.

  • Is X-Post MCP free to use?

Yes, the project is open-source and free to use, but you may incur costs associated with API usage.

  • What technologies does X-Post MCP use?

X-Post MCP is built using Bun, TypeScript, Express, and integrates with the Twitter API and Google Gemini.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
subhadeeproy3902
Star
0
Language
TypeScript
License
MIT license

Recommend Servers

View All
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

13 hours ago
Shippo
@Shippo

21 hours ago