What is io.github.labham-llc/agentcents?

Local LLM cost proxy: forecasts each call and recommends the cheapest model that clears the task.

How do I install io.github.labham-llc/agentcents?

Clone io.github.labham-llc/agentcents from https://github.com/labham-llc/agentcents-skill and configure it as an MCP server in your client (Claude Desktop, Cursor, or VS Code).

What category does io.github.labham-llc/agentcents belong to?

io.github.labham-llc/agentcents is listed under Developer Tools MCP servers on MCPFind.

io.github.labham-llc/agentcents — MCP Server for Developer Tools

agentcents — LLM cost consulting skill for Claude

A Claude Skill that turns Claude into a neutral LLM cost advisor: estimate what any call or agent workflow will cost across candidate models, get the cheapest model that clears the task's capability bar, and see the comparison as a Mermaid diagram — with honest ranges, never false point estimates.

Works two ways:

Consult mode (no install): answers from a bundled, hand-verified snapshot of current model prices and Intelligence Index scores.
Live mode: if the agentcents proxy is running locally, the skill uses your real ledger — calibrated forecasts, spend, and accuracy instead of priors.

Install

Claude.ai / Desktop: Settings → Capabilities → Skills → Add → upload this folder (or the packaged .skill).

Claude Code: /plugin marketplace add labham-llc/agentcents-skill then /plugin install agentcents@labham-skills

Then just ask things like:

what would it cost to classify ~500 support emails a day, about 200 tokens each?

I'm building a 5-step research agent — which model should each step use?

What's in the box

SKILL.md                 — the consulting method (measure, range, bar, pick, flag instability)
assets/pricing.json      — price + capability snapshot (see _meta.verified_utc)
references/local-api.md  — live-mode reference for a locally running agentcents

Snapshot verified: 2026-07-15 (see _meta.verified_utc) — refreshed with each agentcents release.

The product behind it

agentcents is a local proxy that meters, forecasts, and budget-enforces LLM API calls — and grades its own forecasting accuracy on a calibration page. pip install agentcents. The skill is free; so is the agentcents free tier.

Set up in your AI client

AI clientOperating system

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json

{
  "mcpServers": {
    "io-github-labham-llc-agentcents": {
      "command": "uvx",
      "args": [
        "agentcents"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Compatible MCP Clients

io.github.labham-llc/agentcents works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.

Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.

VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.

Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.

Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

io.github.labham-llc/agentcents