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Analyze LLM API costs: token waste detection, caching savings estimates, model comparison
io.github.vpatser1/ai-cost-analyzer is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 93/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding io.github.vpatser1/ai-cost-analyzer to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
npx -y ai-cost-analyzer@1.1.4Review the upstream source before running this command.
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-08-04T07:35:35.161423Z",
"publishedAt": "2026-08-04T07:35:35.161423Z",
"statusChangedAt": "2026-08-04T07:35:35.161423Z"
}
},
"server": {
"name": "io.github.vpatser1/ai-cost-analyzer",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-09-29/server.schema.json",
"version": "1.1.4",
"packages": [
{
"version": "1.1.4",
"transport": {
"type": "stdio"
},
"identifier": "ai-cost-analyzer",
"registryType": "npm",
"registryBaseUrl": "https://registry.npmjs.org",
"environmentVariables": [
{
"name": "LICENSE_KEY",
"isSecret": true,
"description": "License key (emailed after purchase at https://aivp-mcp.vercel.app). Omit for the free trial (3 calls per tool)."
}
]
}
],
"websiteUrl": "https://aivp-mcp.vercel.app",
"description": "Analyze LLM API costs: token waste detection, caching savings estimates, model comparison"
}
}