MCP server for deterministic, zero-dependency context-window math, enabling token estimation, text truncation, and budget reporting without a tokenizer.
Counts LLM prompt tokens and estimates API costs across OpenAI and Anthropic models directly inside MCP-compatible chat clients. Supports exact tokenization for OpenAI models and fallback approximation for Claude when no API key is present.
Local-first MCP server that watches your coding sessions and injects a compact summary at the start of each new session. 85.6% token reduction, SQLite storage, no cloud. Works with Claude Code, Cursor, Cline, and Windsurf.
Brings Claude Code's context compaction to any MCP host, enabling agents to gauge context pressure, summarize history, re-hydrate files, and persist rules across session boundaries.
Provides intelligent context management for AI development sessions, allowing users to track token usage, manage conversation context, and seamlessly restore context when reaching token limits.