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"Interacting with Grok Shared Links" matching MCP servers:
- AlicenseAqualityDmaintenanceMCP server that wraps the xAI Grok API, allowing Claude and other AI agents to delegate thinking, planning, and real-time search tasks to Grok. It provides a single tool with options for different use cases including web search, Twitter/X search, and multi-agent reasoning.Last updated221MIT
- AlicenseAqualityBmaintenanceUse XAI's latest api functionalities with Grok MCP. It supports image understanding and generation, live search, latest models and more.Last updated2241MIT
- AlicenseAqualityBmaintenanceMCP server for AI agent affiliate attribution and commission tracking. 7 tools for program discovery, conversion tracking, attribution token verification, and commission queries.Last updated7MIT
- AlicenseAqualityBmaintenanceMCP server that wraps the Grok CLI to enable code review, adversarial testing, and chat with xAI's Grok model, integrating into any MCP host as a peer reviewer, adversary, and consultant.Last updated41628MIT
- FlicenseBquality-maintenanceIntegrates Grok AI into Claude Code to enable real-time X/Twitter search and deep analysis of social media links. It supports a dual-mode architecture featuring a browser-based free mode for SuperGrok subscribers and a cost-controlled API mode.Last updated2221
- Alicense-qualityDmaintenanceConnects Claude Code to xAI's Grok for real-time web and X (Twitter) search with multi-agent architecture and 2M token context.Last updated39152MIT
cic-mcp-sharedofficial
Flicense-qualityBmaintenanceEnables cross-session memory, weighting, and factory/PR/artifact linking for CIC agents, aggregating multiple sessions to identify promotion candidates.Last updated- Alicense-qualityBmaintenanceA minimal local MCP server that lets Claude Desktop or Claude Code delegate coding tasks to Grok Build running headless as a subagent.Last updated22MIT
- Alicense-qualityBmaintenanceLocal-first memory, pipelines, learning, feedback, and safe code tools for AI coding agents.Last updatedMIT
- Flicense-qualityCmaintenanceEnables AI agents to share persistent memory via an MCP server using SQLite, supporting multi-tenant, categorized knowledge with TTL and semantic links, without requiring vector databases.Last updated
- Flicense-qualityDmaintenanceEnables searching X (Twitter) using the xAI Grok API to get summarised answers with citations. Supports filtering by handles, date range, and image/video understanding.Last updated2
- Flicense-qualityBmaintenanceAggregates multiple shared MCP servers into a single HTTP gateway, providing a unified, observable, and reusable MCP access layer for multiple AI clients like Codex, OpenCode, and OpenClaw. It centralizes configuration management, logging, health checks, and circuit breaking to simplify multi-client MCP deployments.Last updated5
- AlicenseAqualityCmaintenanceMCP server for generating and editing images using xAI's Grok image model, supporting text prompts, batch generation, local files, and optional proxy configurations.Last updated2929MIT
- AlicenseAqualityBmaintenanceGrok asked for MCP on a URL. This is it. First MCP server built for Grok URL-based • Zero config • Just worksLast updated81291617MIT
- AlicenseAqualityDmaintenanceMCP server for shared context caching with trust verification -- AI agents share and verify computed results to reduce token cost and increase reliability.Last updated81MIT
- AlicenseAqualityDmaintenanceEnables real-time search of X.com (Twitter) posts, users, threads, and trends via xAI's Grok API, directly from Claude.Last updated54MIT
- AlicenseBqualityDmaintenanceEnables interaction with the Grok AI through an MCP server, supporting chat completions, text completions, embeddings, and model operations with streaming capabilities.Last updated5227MIT
- AlicenseBqualityDmaintenanceProvides seamless access to Grok AI models through the Model Context Protocol by wrapping the official Grok CLI, offering tools for general queries, multi-turn conversations, and code generation.Last updated37MIT
- AlicenseBqualityDmaintenanceProvides a shared context layer for AI agent teams to improve token efficiency through context deduplication and incremental state sharing. It enables multiple agents to coordinate tasks, share real-time discoveries, and manage dependencies while significantly reducing redundant data transmission.Last updated1507MIT