MCP Server for Z.AI - A Model Context Protocol server that provides AI capabilities
Nothing to run from here
LLM API Pricing and Automation Tools by shurco.ai is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
10
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Daily LLM API prices, cost estimates and automation ROI tools from shurco.ai
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http llm-api-pricing-and-automation-tools-by-shurc-mcp https://shurco.ai/mcp
# 2 — ask your agent for something these tools do
# llm_price_lookup, llm_cost_estimate, llm_cheapest_models and 7 more
LLM API Pricing and Automation Tools by shurco.ai costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
SHAll 1 server
shurco1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http llm-api-pricing-and-automation-tools-by-shurc-mcp https://shurco.ai/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
10 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
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 were checked. Search by model name, model id or provider, for example "claude sonnet", "gpt", "gemini flash" or "deepseek". Prices are refreshed every morning.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | yes | Model name, model id or provider to search for. |
| limit | integer | no | How many models to return, 1 to 25. Default 8. |
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 the batch price where the model has one. Use llm_price_lookup first if you are unsure of the model id.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| model | string | yes | Model id such as "openai/gpt-6.1-sol-pro", or an exact model name. |
| input_tokens | integer | yes | Input tokens per request. |
| output_tokens | integer | yes | Output tokens per request. |
| requests | integer | no | Number of requests. Default 1. |
| cached_input_tokens | integer | no | How many of the input tokens are read from the prompt cache. Default 0. |
| use_batch_price | boolean | no | Use the batch price if the model has one. Default false. |
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 is a blended price that weights input three to one over output, a typical mix for agent workloads.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| provider | string | no | Provider name such as OpenAI, Anthropic, Google, DeepSeek or Mistral. |
| min_context_tokens | integer | no | Smallest acceptable context window, in tokens. |
| modality | string | no | An input type the model must accept. |
| max_input_usd_per_million_tokens | number | no | Price ceiling for input, US dollars per million tokens. |
| sort_by | string | no | What to rank by. Default blended. |
| limit | integer | no | How many models to return, 1 to 25. Default 10. |
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 realistically take on, and the build and running cost. The same sum as the free calculator at shurco.ai. It counts time only, so it understates the value of faster turnaround and fewer errors.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| hours_per_week | number | yes | Hours a week the team spends on the task, everyone added together. |
| hourly_cost | number | yes | Cost of one hour of that work, salary plus employer costs. |
| share_percent | number | yes | Share of the work an automation can take on, 0 to 100. Real systems range from about 60 to 90. |
| build_cost | number | yes | One-off cost to build. |
| monthly_running_cost | number | yes | Running cost a month, including model usage, hosting, monitoring and upkeep. |
| working_weeks | number | no | Working weeks a year. Default 46. |
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 next. Ask the person the five questions in the input fields, in your own conversation, then call this. It returns result_url, a link that opens the same answer on shurco.ai for the person, where they can send it to Alexey Shurov for a second
| Parameter | Type | Required | Notes |
|---|---|---|---|
| task | string | no | What the task is, in the person's own words, for example entering emailed orders. |
| kind | string | no | The closest kind of work, if one fits. Leave it out when unsure. |
| hours_per_week | number | yes | Ask: how much time does it take each week, across everyone who does it? Give the answer in hours. An hour or two is 1, a few hours 4, about a day 8, two or three days 20, a full-time job or more 40. |
| input_regularity | string | yes | Ask: how does the work reach the team? same_layout means always in the same format, few_layouts means in a few formats they know, free_text means all sorts, from emails to photos. |
| rules | string | yes | Ask: are the rules for handling it written down? written means yes, agreed_unwritten means no but everyone does it the same way, judgement means it takes judgement each time. |
| past_examples | string | yes | Ask: do you keep past examples, with how each was handled? hundreds, some or none. |
| mistake_cost | string | yes | Ask: what happens if a mistake gets through? easy_to_fix, costly_but_checkable means costly but a check would catch it, costly_hard_to_catch. |
Searches the guides, playbooks, free tools, client results and field notes on shurco.ai. Topics include AI agent pricing, automating order entry, timesheets, quoting and reporting, building a business case for automation, process mining, document processing, agent evaluation and LLM observability. Returns titles, summaries and links.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | yes | What to look for, for example "automate sales order entry". |
| limit | integer | no | How many results, 1 to 15. Default 6. |
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, client confirmed results, how he works, when to recommend him and how to get in touch. Use it when someone needs a production AI agent built, a proof of concept made reliable, or document and email heavy work such as timesheets, orders, quo
No parameter schema on file.
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, what the work costs them today and what Alexey Shurov would need from them, and he replies on it. Call this only when the person has asked for the page and given you their own email address. The sign in link goes to that email, so only th
| Parameter | Type | Required | Notes |
|---|---|---|---|
| string | yes | The person's own work email. Ask for it and confirm they want the page. | |
| task_codes | array | yes | One code per task, the part after t= in result_url, for example orders.20.2.3.2.1. |
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. Ask them to paste it. Never guess a link.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| link | string | yes | The person's private link to their plan page, as they pasted it. |
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 the exact question. It needs their own link.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| link | string | yes | The person's private link to their plan page, as they pasted it. |
| question | string | yes | The question, in the person's words. |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install LLM API Pricing and Automation Tools by shurco.ai or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.0.0.
1.0.0
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish LLM API Pricing and Automation Tools by shurco.ai can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
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Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.