MCP server that wraps the Dagster GraphQL API — manage runs, assets, schedules, sensors, and backfills from any MCP client
Nothing to run from here
Lingshu Solver 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.
93/100
trust score
13
downloads a day
local
or remote
3k
downloads in 30d
What it does
Deterministically verifiable real root calculation (MCP) tool: a mathematical tool for AI agents that will not make mistakes in calculations (non-large models, zero illusion).
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user lingshu-solver-mcp '--' npx -y lingshu-solver
# 2 — ask your agent for something these tools do
# solve, give_feedback, poly_roots and 2 more
Lingshu Solver costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
GPAll 3 servers
genesis-plan3 servers
3 categories
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. This one can run either way — at an address its publisher runs, or as a process under your own user, with your files and your network — and this marketplace is in the path of neither.
Claude Codedeclared by this listing
This is a public server: you run it yourself and this marketplace is not in the path. You need Node.js — the current LTS (24) is the safe choice; npx comes with it. Claude Code registers it in one command; --scope user makes it available in every project. The '--' is in quotes so that PowerShell passes it on.
claude mcp add --scope user lingshu-solver-mcp '--' npx -y lingshu-solverReconnect, or start a new session, and the tools appear in the model’s tool list.
Or connect to its publisher’s address
Its publisher also runs it at https://hongchenlingjing.com/mcp: nothing to start on your machine, and this marketplace is not in the path.
claude mcp add --scope user --transport http lingshu-solver-mcp https://hongchenlingjing.com/mcpFree on mcprush, and it runs from its publisher’s own package: 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 your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.
What you approve
5 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.
求解实数方程组的确定性数值引擎（非大模型，无随机、同输入输出可复现）。适用：需可验证、可复现的实数解（代数或 sin/cos/tan/log/exp/sqrt/abs 等常见超越函数），尤其给 AI Agent 当"不会胡说"的数学后端。不适用：纯符号推导/闭式证明、微分方程初值问题、整数/必不等于等强制约束（暂不支持）。输入：equations 为含 "=" 的方程字符串数组，如 ["x^2+y^2=25","x+y=7"]；variables 可选（不填自动识别，最多6个）；domain 可选（如 {"x":[-30,30]}），否则默认每变量 ±1e6。硬限制：变量 ≤6；方程 1–64 条且数量须 ≥ 变量数；单次方程文本 ≤100KB；输出固定 6 位小数（不可切换）。输出（JSON）：resultType=empty(严格证无实数解)/finite(有限已验证解)/infini
No parameter schema on file.
AI 智能体在调用 solve 遇到卡点、错误、或认为结果有问题时，主动回报。回报内容仅落本地 feedback.log，不会外传。帮助作者持续改进。
No parameter schema on file.
多项式全部实根，逐个 Krawczyk 认证（带严格误差盒）。输入系数「最高次在前」，如 [1,-2,-5,6] 表示 x³−2x²−5x+6。确定性、可复现、可证明正确；复数根不返回（本品只做实数）。给 AI Agent 当「可靠的多项式求根件」——不会再像通用 LLM 那样把根算错或半对。★ 计费边界（Agent 必读）：与 solve 同规则 —— honorPaid:true 即信任制免费放行；否则走付费通道（GET /pricing）。
No parameter schema on file.
核验一个「声称的答案」到底对不对——这是「LLM 猜了 2.1、真根是精确 2」的检查。输入方程 + 候选值/点（数字，或 {变量:值}，或按 variables 顺序的数组），本工具在候选点邻域内调用同一套认证内核：若找到与之匹配的认证根 → 返回 verified + 误差盒；若找不到 → 返回 refuted 并附上最近的认证根（让 Agent 立刻看到正确值）。确定性、非 LLM、结果可复现。★ 计费边界（Agent 必读）：与 solve 同规则 —— honorPaid:true 即信任制免费放行；否则走付费通道（GET /pricing）。
No parameter schema on file.
对公收款：为本次/后续求解创建一笔真实付费订单（¥0.01/次），返回订单号、专属 key 与结构化付款意图（payIntent）。统一收款入口 = 工银e支付银联聚合码（支持支付宝/微信/银联扫码），钱落公司对公户，不接任何支付平台商户 API。【付款后自助入账·推荐】付款完成后再调一次本工具并传 orderId + selfReportPaid:true，即立即入账、立即放行，不需要任何人工核对、不需要等对账 —— 本服务按信任制运转（同一道门 honorPaid 本来就免费，所以「声明已付款」不会多出任何损失，只是把诚实付款的人从「等入账」里解放出来）。若服务端未配置收款方式（LS_PAY_TO 为空），订单仍可创建但 payIntent.payTo 为 null，此时请改用 honorPaid:true 或联系作者。
No parameter schema on file.
Free
$0 forever
- Every tool, no call limit
- No card, and mcprush charges nothing for it
- Source is public; its licence metadata reads NOASSERTION rather than naming a licence
- Runs on your machine — nothing of it reaches our gateway
- 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 Lingshu Solver or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
Alert at 80% · then the tool returns a normal MCP error
Used this month: —
ATrust score 93 / 100
Release 1.0.25 · scanned 14 Oct 2026
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.
Threat score100
Client score93
Findings2 threat · 0 capability
Capabilityhigh
Coveragesource
Verificationrepo
Surface digeste652f4dff03ef8d0e613d0b290973f0a53f44d1af33b1e85839c5c730d9bc414
Score vectorthreat 100 → client 93
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | high | capability blast radius (high) — client exposure if the model is manipulated | −6 |
| verification-discount | repo | publisher verification (public source) — no provenance, but the source is public and inspectable | −1 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tool surfaceread
Implementation sourceread
Package metadataread
Live transportnot available
Tools were statically extracted from the published source (5 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. high is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| solve | no tags | |
| give_feedback | no tags | |
| poly_roots | no tags | |
| verify | no tags | |
| pay | no tags |
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
Integrityfirst-seen
Surface digeste652f4dff03ef8d0
Scanned2026-10-14
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
Always latest — the install command names no version, so it installs the newest release when it runs; the current release on file is 1.0.25. Pin a release below and the command asks for exactly that one.
1.0.25
14 Oct 2026
latestNo release note was published with this version.
1.0.24
13 Oct 2026
No release note was published with this version.
1.0.23
7 Oct 2026
No release note was published with this version.
1.0.22
2 Oct 2026
No release note was published with this version.
1.0.15
undated
- The version this listing was on when mcprush began following its releases. The registry was not asked when it shipped, so this row carries no date.
—
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 Lingshu Solver 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.