# Shurco Llm Pricing MCP server

Source: https://glimind.com/server/mcp-registry%2Fai.shurco%2Fllm-pricing
Registry id: `mcp-registry/ai.shurco/llm-pricing`
Status: live (checked 2026-10-27T03:18:52.769Z)

## Verdict

Shurco Llm Pricing MCP server answered 100% of Glimind's liveness checks over 30 days, better than 42% of MCP servers, with 500 ms median handshake and 0 outages in 90 days. Its agent-readiness grade is A (96/100) across 10 tools, costing an agent about 2,593 tokens to load. Checked every few minutes; no tool is ever called.

## Measurements (30 days)

| Metric | Value | Better than |
|---|---|---|
| Uptime, 30 days | 100% | 42% of MCP servers |
| Median handshake latency | 500 ms | 50% of MCP servers |
| p95 handshake latency | 3540 ms | — |
| Checks in 30 days | 2,981 | — |
| Outages, 90 days | 0 | — |
| Median recovery | — | — |
| Agent-readiness score | 96/100 (A) | 82% of MCP servers |
| Tools | 10 | — |
| Tool-list size for an agent | ~2,593 tokens | 49% of MCP servers |
| Days observed | 14 | — |

## Install

```json
{
  "mcpServers": {
    "shurco-llm-pricing-mcp-server": {
      "type": "http",
      "url": "https://shurco.ai/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http shurco-llm-pricing-mcp-server https://shurco.ai/mcp
```

## Tools (10)

- `about_alexey_shurov`: Who runs shurco.ai. Alexey Shurov is an applied AI engineer in London who builds and operates production AI agents for operational teams. Returns what he does, 
- `ask_alexey_on_plan_page`: Adds a question to a person's plan page on shurco.ai, in their name. Alexey Shurov is told and replies on the page. Use it only when the person has agreed to th
- `automation_roi`: Payback period and three year net for automating a repetitive task. Give the hours a week the team spends on it, what an hour costs, the share an automation can
- `llm_cheapest_models`: The cheapest models that meet your constraints, ranked by price. Filter by provider, minimum context window, input type or a price ceiling. The default ranking 
- `llm_cost_estimate`: Cost in US dollars of calling one model, from the tokens in and out per request and the number of requests, at today's price. Handles cached input tokens and th
- `llm_price_lookup`: Today's API price for one or more large language models, in US dollars per million tokens, with cached and batch prices, context window and the date the prices 
- `open_plan_page`: Makes a private plan page on shurco.ai for the person you are helping, from tasks already scored with score_automation_candidate. The page holds the first steps
- `read_plan_page`: Reads a private plan page on shurco.ai as plain text, so you can explain it to the person it belongs to. It needs the person's own link, which only they have. A
- `score_automation_candidate`: Scores one repetitive business task out of 14 for how good a first AI automation it would be, and says in plain words what helps, what to watch and what to do n
- `search_shurco`: Searches the guides, playbooks, free tools, client results and field notes on shurco.ai. Topics include AI agent pricing, automating order entry, timesheets, qu

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.