"Documentation URL for a service API, data, and LLM usage" matching MCP servers:

A local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen, DeepSeek) alongside Anthropic and OpenAI.

Enables agents to detect and redact PII and secrets in text, HTML, and PDF documents before they reach an LLM, with reversible placeholder, mask, or hash redaction, and to list supported detectors and redaction styles.

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

MCP server that reads local OpenClaw session files to provide token usage and cost data without any network calls or authentication.

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.

Enables a primary agent to offload bounded, high-volume analysis of explicitly selected workspace files to an auxiliary LLM through a single read-only tool, returning text, Markdown, JSON, or unified-diff output with token usage while retaining all planning, verification, and edits.

Enables importing AI provider usage CSVs or syncing OpenRouter/OpenAI costs into a local SQLite ledger, then querying spend, budgets, and invoice-style summaries via MCP tools.

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.

Token cost math for LLM API calls: current per-million-token rates for 69 models across 17 providers, with local arithmetic for estimates, comparisons and monthly budgets. Rates are verified and date-stamped.

A local-first LLM routing MCP server that keeps sensitive data on your own models, with fail-closed privacy and manager-worker delegation, exposing route and complete tools to any MCP client.

Provides real-time LLM pricing and availability data as an MCP server, enabling AI agents to make optimal model routing decisions at inference time with cited pricing sources.

Lets MCP clients delegate private or bulk text tasks to a local OpenAI-compatible LLM while keeping data on the machine.

Independent latency and uptime data for 46 hosted AI inference APIs, probed every 5 minutes from 4 regions with no gateway, plus a verified model deprecation calendar and Claude Code / Codex speed and accuracy drift. Four read-only tools, no API key; data CC BY 4.0.

MCP server that provides tools for evaluating LLM agent reliability, including adversarial task generation, automated LLM-as-judge assessment, and confidence statistics.

Enables AI agents to check URL safety before fetching content, using Google Web Risk, URLhaus, PhishTank, and AI analysis to return SAFE/SUSPICIOUS/DANGEROUS verdicts.

Enables cloud-based MCP clients to delegate privacy-sensitive or large-output tasks to a local LLM, returning sanitized placeholders or digested summaries so private data never leaves the user's network.

Enables MCP clients to send raw text prompts to inexpensive LLM models via the Devin/Windsurf backend, returning answers in result files to avoid context bloat, with support for multi-turn sessions and model discovery.

Daily-verified LLM API pricing dataset (44+ models, CN & global) with a hosted MCP server for live price queries and token cost estimation.

A local MCP gateway that unifies multiple LLM providers, API keys, routing, and multi-model discussions into a single tool surface.

MCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.