Exports the AI Context file for a given master, combining network state and CLI commands for language model planning.
Apache 2.0
735,836 tools. Updated 2026-11-02 14:13
"Optimizing AI Model Thinking, Token Usage, and Context Size" matching MCP tools:
- Count tokens in UTF-8 text using Algenta tokenizer models for prompt-size checks and token budgeting. Deterministic and read-only; returns token count and resolved model details.Apache 2.0
- Execute a single AI model call to test prompts before building full workflows. Returns output, token usage, estimated provider cost, and trace URL.MIT
- Execute multi-step AI workflows with reduced context usage by keeping intermediate results in the workflow engine, supporting multiple model calls and tool integrations.MIT
- Returns context consumption statistics for the current session: total bytes, per-tool breakdown, call counts, token usage, and savings ratio.Elastic 2.0
- Generate a signed token proving human authorization for a specific AI agent action, embedding action details, context, and expiry for verification before execution.MIT
Matching MCP Servers
- AlicenseAqualityCmaintenanceExposes 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.125 npmMIT
- AlicenseCqualityDmaintenanceEnables 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.18MIT
Matching MCP Connectors
Cloudflare Workers MCP server: ai-model-router
Live pricing data for AI models across vendors: input/output prices per 1k tokens as JSON.
- Query x402 consumption records for any EVM wallet address. Get per-call details including model, token usage, credits, USD paid, transaction hash, and timestamp — no login needed.MIT
- Execute LLM requests by burning Shells to get AI-generated responses with calculated costs based on model and token usage.-
- Ask general or specialist questions and get generated text from a selected domain and model tier. Enforces plan, tenant policy, token allowance, and usage metering.Apache 2.0
- Retrieve your account's AI model limits and tier configuration, including subscription tokens, context limits, and account constraints like repository and file caps.MIT
- Retrieve token usage and cost breakdown for a specific run, detailed by agent and model.MIT
- Record compact model token usage for value proof. Capture input, output, cached, and total tokens, cost, latency, and provider details while excluding sensitive content.MIT
- Retrieves detailed metadata for a specified model, including family, parameter size, quantization, context length, and layer architecture. Omitting provider queries live local providers.Creative Commons Attribution Non Commercial No Derivatives 4.0 International
- Send OpenAI-compatible chat completion requests to the Badgr API and receive replies with token usage; max_tokens is capped at 4096 and usage is metered.Apache 2.0
- Inspect the caller's queued work and recorded model usage to check job progress and track token consumption.Apache 2.0
- Track AI token usage and estimated cost for the current MCP session, covering calls from design analysis, documentation, and composition tools.MIT
- Query any AI model with a prompt and receive its response with metadata including latency and token usage. Optionally limit response tokens with automatic distillation.MIT
- Compare AI model performance by testing 1-5 models simultaneously with identical prompts. Get output text, latency, token usage, and cost estimates for informed model selection.MIT
- Check billing cycle usage broken down by model: cost, request count, and token totals, to pinpoint cost drivers.MIT
- Retrieve managed AI gateway token counts, response count, and exact USD cost per model for a project. Use to report spend or identify the dominant model.MIT
- Retrieve a paginated per-model analytics breakdown with request counts, costs, token usage, and group totals to compare model cost, popularity, and efficiency; Enterprise plans only.MIT