An MCP server that gives orchestrator agents fine-grained control over interactive Claude Code sessions running inside tmux, enabling mid-session steering, interruption, and token-efficient result extraction.
Monitors your Cursor usage and provides a conserve flag to the agent, helping you manage request quota by batching questions, preferring defaults, and cutting unnecessary confirmations.
Enables analysis of YouTube videos using the Gemini API to generate summaries and answer specific questions via direct URLs. It supports standard videos and shorts, allowing users to interact with video content without requiring manual downloads.
Enables AI assistants to query live football data, including fixtures, live scores, standings, statistics, betting odds, and full odds movement history for corner and card lines.
Post-hoc session handoff and project memory for Claude Code: MCP tools list_sessions and handoff turn any session β even crashed or usage-limit-hit ones β into a clean handoff.md another model can continue from, with secrets redacted from every output. Zero dependencies, fully local; also distills a project's entire session history into one cited memory brief.
Enables running a Model Context Protocol server with a validated echo tool over stdio or Streamable HTTP, including strict schemas, tests, and hardened container deployment.
Provides context management and todo persistence with AI second opinions from ChatGPT and Claude. Enables saving code snippets, conversations, and todos across sessions with full-text search capabilities.
Full-stack utility API with 337+ tools including AI chat, web scraping, weather, finance, SEO, crypto, colors, readability, DNS, and more β all through a single MCP server. Pay-as-you-go credits, no API keys needed.
Enables searching and retrieving Claude Code conversation history via hybrid semantic and keyword search, allowing the agent to access its own past interactions.
Relays messages between two Claude Code sessions running on separate machines, using the Channels API to push an incoming message directly into the other session so one session can ask another about its own checkout. Each message carries an id and is tracked as sent, delivered-to-process, or answered, with a per-message reply budget.
Enables AI agents to perform common utility tasks through a streamable HTTP MCP endpoint, including JSON inspection, regex testing, cron parsing, hashing, base64 encoding/decoding, URL analysis, color conversion, text diffing, CSV parsing, JWT decode/verification, Markdown-to-HTML rendering, and UUID/token generation without API keys.