Daily LLM token pricing data with automatic updates
Local observability CLI for LLM usage — token costs, mascote, MCP server. Offline-first.
> A local-first AI CLI for understanding code in your repo. > Private by default. No token costs. No cloud.
Claude Code usage dashboard — token costs, quota cycle tracking, cache efficiency, multi-machine sync across all your devices
Cost prediction for AI agents. Estimate token costs before execution, review spending after.
MCP server that analyzes your MCP setup: token costs, bloated schemas, duplicate tools, and optimization tips
AI Observability & Cost Intelligence — track token costs, latency, and hallucination risk for every LLM call
Reduce token costs by compressing long conversations while preserving useful recent context.
Automatic prompt caching for Claude Code. Cuts token costs by up to 90%.
Cost prediction for AI agents. Estimate token costs before execution, review spending after.
Reduce LLM token costs by 30-60% with TONL format. TypeScript library & CLI with MCP Server for bidirectional JSON/YAML ↔ TONL conversion.
CLI tool for collecting Claude Code session analytics. Parses local `.jsonl` session files, calculates token costs, and sends daily metrics to your team's analytics API.
MCP server for Claude Code × Kimi K2.5 (256K context) — delegate bulk codebase analysis to Kimi, save 90% on token costs
Cut AI Agent token costs by 96%. Chains multiple tool calls into a single TypeScript code execution in a secure sandbox.
Costea Web UI — visualize AI agent token costs, session analytics, and cost predictions.
Run **Gemma** and other LLMs **fully on-device** in your Expo / React Native app — no API keys, no cloud, no per-token costs, complete user privacy.
Monitor Claude Code JSONL usage logs, estimate token costs, and notify on threshold breaches.
Scan, redact, and squeeze code before it reaches an LLM. Blocks API keys, secrets, and PII in real time. Cuts token costs 30–70% with smart compression. Git hooks, CI/CD, SARIF, watch mode. Free for personal use — commercial license for teams.
Intelligent video analysis powered by OpenAI Vision API. Extract frames, analyze content, search videos semantically, and estimate token costs with FFmpeg and GPT-4/GPT-5 models.
Compress AI prompts from your terminal — reduce LLM token costs by up to 60%
SDK for estimating and reconciling LLM token costs using a credit system.
Self-learning MCP proxy. Watches your Claude Code usage, generates optimized proxies, cuts token costs by 99%.
Calculate LLM token costs from llmlite pricing data
Efficient TickTick MCP - LLM-optimized task management with intelligent time handling and 70% lower token costs
LLM Token Cost Monitor
A Rails engine for monitoring Claude Code usage, calculating costs using LiteLLM pricing, and displaying usage analytics in your Rails app
A simple Rails engine to log API usage from multiple LLM providers and provide methods for tracking user consumption over time, enabling easy rate-limiting.
Captures LLM token usage metrics per task for cost attribution and intelligent routing
Official Ruby client for Blackman AI - The AI API proxy that optimizes token usage to reduce costs
llm_optimizer reduces LLM API costs by up to 80% through semantic caching, intelligent model routing, token pruning, and conversation history summarization. Strictly opt-in and non-invasive.
Logs every call your Rails app makes to OpenAI, Anthropic, Gemini, RubyLLM, or an OpenAI-compatible API: tokens, cost, latency, tags. Calls go straight to the provider — no proxy. Includes price sync, budget guardrails, and a mountable dashboard.
Transforms your local ~/.claude/ session data into a beautiful btop-style terminal dashboard — streaks, tool usage, token costs, work modes, and activity heatmaps. No cloud, no API calls.
Call LLMs from Axn actions using RubyLLM, with structured error handling, optional JSON mode, and cost/token tracking.
Self-hosted error observability and LLM tracing. Captures errors, deduplicates via fingerprinting, and traces AI/LLM calls (token usage, costs, latency). Zero external runtime dependencies.
Welcome to the WhatsApp API from Meta. Individual developers and existing Business Service Providers (BSPs) can now send and receive messages via the WhatsApp API using a cloud-hosted version of the WhatsApp Business API. Compared to the previous solutions, the cloud-based WhatsApp API is simpler to use and is a more cost-effective way for businesses to use WhatsApp. Please keep in mind the following configurations: | Name | Description | | --- | --- | | Version | Latest [Graph API version](https://developers.facebook.com/docs/graph-api/). For example: v13.0 | | User-Access-Token | Your user access token after signing up at [developers.facebook.com](https://developers.facebook.com). | | WABA-ID | Your WhatsApp Business Account (WABA) ID. | | Phone-Number-ID | ID for the phone number connected to the WhatsApp Business API. You can get this with a [Get Phone Number ID request](3184f675-d289-46f1-88e5-e2b11549c418). | | Business-ID | Your Business' ID. Once you have your Phone-Number-ID, make a [Get Business Profile request](#99fd3743-46cf-46c4-95b5-431c6a4eb0b0) to get your Business' ID. | | Recipient-Phone-Number | Phone number that you want to send a WhatsApp message to. | | Media-ID | ID for the media to [send a media message](#0a632754-3788-43bf-b785-ac6a73423d5a) or [media template message](#439c926a-8a6c-4972-ab2c-d99297716da9) to your customers. | | Media-URL | URL for the media to [download media content](#cbe5ece3-246c-48f3-b338-074187dfef66). |
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