MCP Server for Z.AI - A Model Context Protocol server that provides AI capabilities
Nothing to run from here
LLM Abacus 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.
2
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Compare up-to-date pricing for 40+ LLMs (incl. Chinese) & estimate cost from tokens. EN/zh.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http llm-abacus-mcp https://llmabacus.com/api/mcp
# 2 — ask your agent for something these tools do
# query_model_price, estimate_cost
LLM Abacus costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
LCAll 1 server
llmabacus.com1 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-abacus-mcp https://llmabacus.com/api/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
2 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.
查询指定大模型（如 GPT-5, Claude, DeepSeek）的最新 API 输入、输出和缓存输入单价（单位：每百万 tokens）。
| Parameter | Type | Required | Notes |
|---|---|---|---|
| model | string | yes | 模型 ID 或模糊名称，大小写不敏感（例如 'gpt-5'、'deepseek-v4'、'claude-sonnet'）。匹配顺序：精确匹配 ID → 精确匹配名称 → 按包含关系匹配 ID → 按包含关系匹配名称，取首个命中。 |
估算一段文本或指定 token 数在某个大模型上的输入侧调用成本，以人民币 ¥ 计价。text_or_tokens 支持两种模式：传自然语言文本时自动估算 token 数（中文按字符、英文按词分别计），传纯数字字符串时直接作为已知 token 数使用。返回：所用估算方法、token 数、按原价计的输入成本；若该模型提供缓存输入价，另给出缓存命中成本、相对原价的节省百分比与倍数差价；末尾附该模型的输入 / 输出 / 缓存输入单价（每百万 tokens）。⚠️ 本工具只计算输入成本，不含输出 token 费用——要估算完整往返成本，需另取输出单价自行相加。
| Parameter | Type | Required | Notes |
|---|---|---|---|
| model | string | yes | 模型 ID 或模糊名称，大小写不敏感（例如 'deepseek-v4-pro'、'gpt-5'、'claude-sonnet'）。匹配规则与 query_model_price 一致；不确定名称时可先调 query_model_price 确认。 |
| text_or_tokens | string | yes | 二选一：① 待估算的自然语言文本（如一段提示词或整篇文档），工具按中文字符 + 英文词估算 token 数；② 纯数字字符串表示已知 token 数，如 '200000'。注意：整串都是数字时一律按模式 ② 处理——若确实要估算一串数字本身的 token 数，请混入任意非数字字符。 |
| time_band | string | no | 分时模型的计费时段。缺省为 peak（峰时/最坏价，避免低估）；只有确认调用发生在官方空闲时段时才传 off_peak。 |
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 Abacus 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 Abacus can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
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.