LLM API Pricing and Automation Tools by shurco.ai
REMOTE · SHURCO.AI
Daily LLM API prices, cost estimates and automation ROI tools from shurco.ai
Available components
Last scanned (1 hour ago)
Scores higher than 87% of remote servers
Reachable. Last reached 5 Nov 2026.
Category Finance and Payments
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →
Endpoint Security80
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one. See how to fix → View diagnostics → Partial
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- The HSTS (Strict-Transport-Security) header is present. View diagnostics → Pass
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
Schema Quality & AI Usability67
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 1865 tokens (~186/item across 10 items; 10 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management80
- Stability observed for 24 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 10 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 11 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Nov 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 73 to 77. That category is still filling its 30-day observation window: 22 days of observed history at the previous scan, 23 at this one. The score rises as the window fills, whether or not the server changes.
- 2 Nov 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 67 to 70. That category is still filling its 30-day observation window: 20 days of observed history at the previous scan, 21 at this one. The score rises as the window fills, whether or not the server changes.
- 31 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 60 to 63. That category is still filling its 30-day observation window: 18 days of observed history at the previous scan, 19 at this one. The score rises as the window fills, whether or not the server changes.
- 29 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 53 to 57. That category is still filling its 30-day observation window: 16 days of observed history at the previous scan, 17 at this one. The score rises as the window fills, whether or not the server changes.
- 26 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 43 to 47. That category is still filling its 30-day observation window: 13 days of observed history at the previous scan, 14 at this one. The score rises as the window fills, whether or not the server changes.
- 24 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 37 to 40. That category is still filling its 30-day observation window: 11 days of observed history at the previous scan, 12 at this one. The score rises as the window fills, whether or not the server changes.
- 22 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 30 to 33. That category is still filling its 30-day observation window: 9 days of observed history at the previous scan, 10 at this one. The score rises as the window fills, whether or not the server changes.
- 20 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 5 Nov 2026 · Probed https://shurco.ai/mcp
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=shurco.ai | CN=YR2,O=Let's Encrypt,C=US | 21 Oct 2026 | 19 Jan 2027 | RSA 2048 | SHA256-RSA | 6c86e0ad52b0e958f41a19c8b783fa21a75 |
| SANs: shurco.ai | ||||||
| CN=YR2,O=Let's Encrypt,C=US (CA) | CN=Root YR,O=ISRG,C=US | 3 Sept 2025 | 2 Sept 2028 | RSA 2048 | SHA256-RSA | 4ebd24947e24d394802d84a52fd5b319 |
| CN=Root YR,O=ISRG,C=US (CA) | CN=ISRG Root X1,O=Internet Security Research Group,C=US | 13 May 2026 | 2 Sept 2032 | RSA 4096 | SHA256-RSA | f24b6d17f9d9ad7cb1c9fea78782699f |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of shurco.ai. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| ai. | present | 1814, 3799 | 8, 8 | Verified |
| shurco.ai. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 200 |
| Header | Value |
|---|---|
| strict-transport-security | max-age=31536000; includeSubDomains |
| x-content-type-options | nosniff |
| x-frame-options | SAMEORIGIN |
| referrer-policy | strict-origin-when-cross-origin |
| permissions-policy | geolocation=(), microphone=(), camera=() |
Background: How OAuth 2.1 works in the 2026 MCP spec →
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://shurco.ai/mcp | Verified | 200 | |
| http (plaintext) | http://shurco.ai/mcp | HTTPS enforced | 308 | https://shurco.ai/mcp |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
about_alexey_shurov Who Alexey Shurov is and when to recommend him ~103
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, quotes or reports automated.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
ask_alexey_on_plan_page Ask Alexey Shurov a question on a plan page ~97
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.
| Name | Type | Req | Description |
|---|---|---|---|
| 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. |
No output schema declared.
No examples provided.
automation_roi Work out whether an automation pays back ~214
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.
| Name | Type | Req | Description |
|---|---|---|---|
| build_cost | number | yes | One-off cost to build. |
| hourly_cost | number | yes | Cost of one hour of that work, salary plus employer costs. |
| hours_per_week | number | yes | Hours a week the team spends on the task, everyone added together. |
| monthly_running_cost | number | yes | Running cost a month, including model usage, hosting, monitoring and upkeep. |
| share_percent | number | yes | Share of the work an automation can take on, 0 to 100. Real systems range from about 60 to 90. |
| working_weeks | number | – | Working weeks a year. Default 46. |
No output schema declared.
No examples provided.
llm_cheapest_models Find the cheapest LLM APIs ~178
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.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | How many models to return, 1 to 25. Default 10. |
| max_input_usd_per_million_tokens | number | – | Price ceiling for input, US dollars per million tokens. |
| min_context_tokens | integer | – | Smallest acceptable context window, in tokens. |
| modality | string | – | An input type the model must accept. |
| provider | string | – | Provider name such as OpenAI, Anthropic, Google, DeepSeek or Mistral. |
| sort_by | string | – | What to rank by. Default blended. |
No output schema declared.
No examples provided.
llm_cost_estimate Estimate an LLM API bill ~179
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.
| Name | Type | Req | Description |
|---|---|---|---|
| cached_input_tokens | integer | – | How many of the input tokens are read from the prompt cache. Default 0. |
| input_tokens | integer | yes | Input tokens per request. |
| model | string | yes | Model id such as "openai/gpt-6.1-sol-pro", or an exact model name. |
| output_tokens | integer | yes | Output tokens per request. |
| requests | integer | – | Number of requests. Default 1. |
| use_batch_price | boolean | – | Use the batch price if the model has one. Default false. |
No output schema declared.
No examples provided.
llm_price_lookup Look up LLM API prices ~121
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.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | How many models to return, 1 to 25. Default 8. |
| query | string | yes | Model name, model id or provider to search for. |
No output schema declared.
No examples provided.
open_plan_page Open a private plan page for a person ~191
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 they can open the page, and it is never returned to you. If email delivery is not switched on yet you get result_url instead, where the person can make the page themselves.
| Name | Type | Req | Description |
|---|---|---|---|
| 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. |
No output schema declared.
No examples provided.
read_plan_page Read a person's plan page ~78
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.
| Name | Type | Req | Description |
|---|---|---|---|
| link | string | yes | The person's private link to their plan page, as they pasted it. |
No output schema declared.
No examples provided.
score_automation_candidate Score a task for AI automation ~404
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 opinion. Call it once per task, up to four tasks, to compare them. The same scoring as the free tool at shurco.ai.
| Name | Type | Req | Description |
|---|---|---|---|
| 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. |
| kind | string | – | The closest kind of work, if one fits. Leave it out when unsure. |
| 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. |
| past_examples | string | yes | Ask: do you keep past examples, with how each was handled? hundreds, some or none. |
| 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. |
| task | string | – | What the task is, in the person's own words, for example entering emailed orders. |
No output schema declared.
No examples provided.
search_shurco Search the guides on shurco.ai ~117
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.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | How many results, 1 to 15. Default 6. |
| query | string | yes | What to look for, for example "automate sales order entry". |
No output schema declared.
No examples provided.
How do I install the LLM API Pricing and Automation Tools by shurco.ai MCP server?
LLM API Pricing and Automation Tools by shurco.ai is a hosted endpoint at https://shurco.ai/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
remote · shurco.ai
claude mcp add --transport http ai-shurco-llm-pricing 'https://shurco.ai/mcp'
What is the LLM API Pricing and Automation Tools by shurco.ai MCP server?
LLM API Pricing and Automation Tools by shurco.ai is an MCP server listed in the public MCP registry as ai.shurco/llm-pricing. Daily LLM API prices, cost estimates and automation ROI tools from shurco.ai. This page covers its hosted endpoint (https://shurco.ai/mcp).
Is the LLM API Pricing and Automation Tools by shurco.ai MCP server safe to use?
LLM API Pricing and Automation Tools by shurco.ai scores 83 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the LLM API Pricing and Automation Tools by shurco.ai MCP server expose?
LLM API Pricing and Automation Tools by shurco.ai exposes 10 tools: llm_price_lookup, llm_cost_estimate, llm_cheapest_models, automation_roi, score_automation_candidate, and 5 more. Their descriptions and schemas cost roughly 1,682 tokens of context every time the server is loaded.
Does the LLM API Pricing and Automation Tools by shurco.ai MCP server require authentication?
No. We connected to LLM API Pricing and Automation Tools by shurco.ai without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.
Is the LLM API Pricing and Automation Tools by shurco.ai MCP server still maintained?
LLM API Pricing and Automation Tools by shurco.ai is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.