"Optimizing AI Model Thinking, Token Usage, and Context Size" matching MCP servers:

Exposes a get_context_usage tool that reports raw token usage from session transcripts for Claude Code and OpenAI Codex CLI, enabling agents to check context size and branch behavior.

Enables access to Usage and Billing APIs for managing accounts, products, meters, plans, and usage reporting. Supports operations like creating products/plans, reporting usage, and retrieving billing information.

Enables coding agents to retrieve token-budgeted, source-hashed code context from explicitly registered local repositories via read-only MCP tools, reducing broad repository crawling while providing structure, symbols, and impact slices.

Enables local-first tracking of AI token usage and costs from Claude Code and OpenCode, answering queries about tokens, models, sessions, and cost through MCP tools and a CLI, with no network calls.

MCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

Read-only MCP server for querying AI usage metrics (exact tokens, cost, latency, errors, productivity) from a local SQLite database, enabling charts and analysis in Claude Code and Cursor.

Enables agents to calculate how many evaluation test cases are needed to trust model comparisons, find the smallest detectable accuracy gap, and assess paired or unpaired results using McNemar and two-proportion statistical tests.

Enables AI agents to compose MCP tool calls into Unix-style pipelines, executing complex workflows server-side and returning only the final result.

Claude Code token usage and cost visibility for MCP-capable agents.

An event-driven MCP server that enables agents to share context streams, publish and subscribe to events, manage tasks, and follow protocols, keeping a fleet of agents mutually context-aware in real time.

Official MCP server for the Wheel Fitment API, giving LLM agents access to vehicle wheel and tire compatibility data, including OEM specs, reverse lookups, plus-sizing calculations, and product card generation.

AI coding usage analytics — track spend, model usage, and costs across Cursor and Claude Code sessions.

MCP server that wraps Cursor Enterprise API to enable AI agents to answer questions about team spending, usage, and model adoption.

A production-ready MCP server template that connects LLMs and AI agents to external data, tools, and services with built-in OAuth 2.1 authentication, Redis-backed session management, and a modular tools engine.

Exposes rate-limit and usage data for AI coding agent CLIs as MCP tools, enabling querying of usage snapshots and reset times.

Lets Claude look up your own Claude subscription usage limits — the same 5-hour and weekly percentages shown by /usage — mid-conversation, so it can pace long tasks and warn you before you hit a wall. It reads the local OAuth login, serves a throttled read-only snapshot (cached with graceful fallback), and exposes it as a single get_usage tool.

Enables AI assistants to see which model IDs each provider's API has started listing since the last check, and to list the models a given provider currently serves with optional substring filtering, all without spending tokens.

A basic Python implementation of a Model Context Protocol server for educational purposes, using FastAPI and WebSockets.

Provides Claude plan usage data (session and weekly percentages) as an MCP tool by reading through a logged-in browser, enabling Claude to check its own remaining usage.

Enables Claude Code sessions to check account rate-limit headroom, local token spend, and live session status, with read-only MCP tools for limits, summaries, token usage, and session listing.

Enables running the same prompt(s) across roughly 300 models from Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Qwen and others, then comparing per-model outputs, latency, token usage, error rates and billed cost side by side. Supports free cost estimates before launching, asynchronous run creation with status polling and cancellation, prepaid x402 credit top-ups, and an optional AI-written comparison summary of the results.

Enables users to retrieve live pricing data for AI models across vendors, including input and output prices per 1k tokens, via a simple API.

MCP server for querying OpenAI usage and cost data, including spend summaries, daily breakdowns, month-over-month comparisons, and token usage by model.

Simple sequential thinking MCP in python

Enables retrieving real Claude subscription usage statistics, including the 5-hour session window, weekly limit, and per-model limits, from the same endpoint Claude Code uses.

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

Provides a comprehensive creative thinking tool with methods like structured process, perspective shift, and constraint-based innovation to enhance divergent thinking.

An MCP server that exposes Claude Code's real-time rate limit usage so that an orchestrator can check remaining capacity before launching subtasks.

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.