Crossmatrix

io.github.praxec由 GitHub 账号 praxec 发布v0.3.4更新于 Oct 24, 2026

Multidimensional House of Quality (QFD) MCP server — cross-dimensional relationship matrices.

概览

AI 生成的概览

Crossmatrix 是一个本地 MCP 服务器,用于多维质量屋(QFD)模型,让助手记录观测并读取矩阵、缺口与报告。

可以做什么
  • 打开、查看并校验模型库,包括状态、描述、校验与导出
  • 声明配置与维度:量表、关系、收缩、维度及成员名册
  • 在单元格上记录观测与证据,弃用成员或关系,写入带版本与审计
  • 读取分析结果:切片、追溯、覆盖率、孤立与下一步缺口、过期来源、冲突与发现
  • 生成 Markdown 质量屋报告,或导出合并后的模型 JSON
  • 在特殊构建中可选地让模型建议观测、新成员或叙述
适用场景
适合让助手协助构建和维护结构化的需求权衡分析,例如质量屋、待办任务、竞品对标、测试覆盖或风险矩阵,并把模型作为可审阅的文件保存在代码仓库中。
运行要求
以本地 stdio 进程运行;推荐用 npx 启动器安装,它会下载并校验平台二进制,或使用预编译二进制安装脚本。需用 init 命令创建模型库。可选的 AI 辅助功能需要特殊构建、显式开启以及 TYPESAFE_JEV_API_KEY 或 OPENROUTER_API_KEY 等密钥。
安装前请注意
服务器会写入项目中的模型目录,包括只追加的审计日志,提交前请检查改动。可选的辅助功能会把成员标签、描述和证据发送给第三方模型服务,并需要 API 密钥;它们只记录建议,不写入分析数值。README 还展示了把远程安装脚本直接通过管道交给 shell 执行的方式。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Crossmatrix,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

crossmatrix

Multidimensional House of Quality (QFD) — cross-dimensional relationship matrices for structured trade-off and requirement analysis. A Rust workspace: crossmatrix (engine) + crossmatrix-mcp (MCP server). Part of Praxec.

Install

npm / npx (recommended for MCP clients)

sh
npx -y @matthew-cochran/crossmatrix --versionclaude mcp add crossmatrix --scope user -- npx -y @matthew-cochran/crossmatrix

The @matthew-cochran/crossmatrix package is a small launcher: on first run it downloads the release binary for your platform, verifies it against the release's checksums.sha256, caches it, and runs it over stdio (signals are forwarded; stdout belongs to MCP). CROSSMATRIX_MCP_BINARY points it at a binary you installed yourself. The package also bundles the agent skills.

Prebuilt binary (no Rust, Cargo, or Git required)

sh
# Linux / macOScurl -fsSL https://github.com/praxec/crossmatrix/releases/latest/download/install.sh | sh
# Windows (PowerShell)irm https://github.com/praxec/crossmatrix/releases/latest/download/install.ps1 | iex

The installer resolves your OS and CPU architecture, downloads the matching release asset, verifies its SHA-256 against the release's checksums.sha256, extracts it safely, and atomically installs the binary into a user-local managed directory ($HOME/.local/bin on Linux/macOS, %LOCALAPPDATA%\Programs\crossmatrix-mcp on Windows). It never compiles from source and fails loudly on an unsupported OS/architecture.

Pin a specific release instead of the current latest stable:

sh
curl -fsSL https://github.com/praxec/crossmatrix/releases/latest/download/install.sh \  | sh -s -- --version v0.3.1

The installer scripts are published as release assets alongside the binaries.

Or download the archive directly. Every release publishes a checksums.sha256 and a machine-readable release-manifest.json listing each target, asset, digest, version, and source SHA:

OSArchTarget tripleAssetBuild supportRuntime smoke tested
Linuxx86_64x86_64-unknown-linux-gnucrossmatrix-mcp-x86_64-unknown-linux-gnu.tar.gznative CInative CI
Linuxarm64aarch64-unknown-linux-gnucrossmatrix-mcp-aarch64-unknown-linux-gnu.tar.gznative CInative CI
macOSx86_64x86_64-apple-darwincrossmatrix-mcp-x86_64-apple-darwin.tar.gznative CInative CI
macOSApple Siliconaarch64-apple-darwincrossmatrix-mcp-aarch64-apple-darwin.tar.gznative CInative CI
Windowsx86_64x86_64-pc-windows-msvccrossmatrix-mcp-x86_64-pc-windows-msvc.zipnative CInative CI
Windowsarm64aarch64-pc-windows-msvccrossmatrix-mcp-aarch64-pc-windows-msvc.zipnative CInative CI

"Native CI" means each asset is built and its MCP initialize/tools/list handshake smoke-tested on that platform's own runner. No other CPU/OS combination is claimed; unsupported platforms are rejected rather than silently cross-compiled.

Updates

Re-run the installer to update. Only the binary in the managed install directory is replaced (atomically); application state and configuration live outside that directory and are never overwritten.

From source

sh
cargo build --release

produces the crossmatrix-mcp MCP stdio server.

Repo-committed models: .crossmatrix/

crossmatrix keeps a model as three documents linked by stable id@version (ADR-0004), plus an append-only audit log, in a directory you commit:

sh
crossmatrix-mcp init            # creates .crossmatrix/ in the current directorycrossmatrix-mcp check           # validates every document and cross-reference
.crossmatrix/  config/<configId>@<version>.json            # methodology: scales, relations, contractions  dimensions/<dimensionSetId>@<version>.json  # dimensions and their members  state/<stateId>.json                        # cells/observations + revision  audit/<stateId>.jsonl                       # one line per accepted mutation (merge=union)

Writes are canonical JSON (sorted keys, 2-space indent, trailing newline) and atomic, so diffs stay small. Findings are computed on every read and never stored. check exits non-zero with path-specific diagnostics (for example state/demo.json: cells[3].to: unknown member 'x' in dimension 'dim_part'); run it in CI.

The server finds its store from, in order: CROSSMATRIX_DIR, the nearest ancestor directory containing .crossmatrix/, $XDG_DATA_HOME/crossmatrix (or ~/.local/share/crossmatrix), then ./crossmatrix-state. model.status reports the resolved root.

CLI

CommandEffect
crossmatrix-mcpserve MCP on stdio
crossmatrix-mcp init [--dir D]create D/.crossmatrix/ (idempotent)
crossmatrix-mcp check [--dir D]validate the store; exit 1 on any problem
crossmatrix-mcp skills install --target <t> (--project D | --user) [--dry-run] [--force]install the bundled agent skills
crossmatrix-mcp skills uninstall --target <t> (--project D | --user) / skills listremove / list installs
crossmatrix-mcp --version / --helpversion / usage

Tools

Two MCP tools, crossmatrix.command (writes) and crossmatrix.query (reads). Every response, including a rejection, carries links to the legal next ops; a rejection's structuredContent is {ok: false, error: {code, message}, links}.

Writes (crossmatrix.command)

json
{"request": {"schemaVersion": "0.2.0", "requestId": "r-17", "modelId": "checkout",  "expectedVersion": 16, "actor": {"actorType": "llm", "persona": "observer"},  "op": {"kind": "observe", "relationId": "rel_need_char", "from": "need_fast",         "to": "char_latency", "observation": "strong", "provenanceClass": "normative"}}}
OpLayerPurpose
model.open—open (or create) state/<stateId>.json; survives restarts
model.status—version, store root, counts
scale.declareConfigurationobservation token → value table
relation.declareConfigurationfrom/to dimensions, relationType, scale, coveragePolicy
contraction.declareConfigurationa chain of relations for derived views
dimension.registerDimensionsan axis (dimensionKind is any snake_case word)
members.syncDimensionsupsert a roster; missing members are deprecated, not deleted; an unchanged roster is a no-op
member.proposeDimensionsadd one member
observeStatea token + evidence on a cell (never a number)
evidence.attachStateadd evidence to an observation
deprecateanyretire a member or relation (supersededBy)

Observation-only: a numeric member weight is accepted only with sourceRef.system (a deterministic import), and a measuredValue only with provenanceClass: observed plus a sourceRef. expectedVersion is an optimistic lock; requestId makes a command idempotent, also across restarts. Each accepted mutation appends one audit line {ts, requestId, actor, op, beforeVersion, afterVersion, summary}.

The legacy one-call flow still works: a command carrying a full model imports it into the session (in memory) for the queries that follow.

Reads (crossmatrix.query)

model.status, describe, slice, trace, explain, coverage, gaps.orphans, gaps.next, stale, conflicts, analyze.marginalize, analyze.contract, analyze.findings, validate, report, export.

  • report {relationId?} returns a Markdown House of Quality: weights, the relationship matrix, the correlation roof (a self-relation), technical importance, targets (attributes.target), coverage and findings with contributors. Without relationId it covers every relation.
  • export {format: model|report|findings} returns the merged model JSON.
  • conflicts {relationId?} lists valence-by-separation tensions and conflicts.
  • trace and slice accept a member id or a sourceRef.uri, page with limit/cursor, and with rollup: true roll leaf observations up a contains hierarchy (a directory implements a feature if any file under it does).
  • stale {hashes?, readFiles?} compares stored source hashes with current ones (readFiles hashes file:// sources inside the project) and returns the changed members plus every cell that references them, paged.

AI assist (optional, off by default)

Two optional cargo features add model-backed helpers. Neither is in the default build or the release binaries unless you build with them, both need an explicit opt-in and a key, and neither ever writes an analysis number: suggestions are recorded as proposed observations that count in no analysis until a human or LLM confirms the cell with an ordinary observe.

sh
cargo build --release --features jev,rigexport CROSSMATRIX_ASSIST=jev,rig            # explicit opt-in (or `all`)export TYPESAFE_JEV_API_KEY=...              # or OPENROUTER_API_KEY (also used by rig)
QueryFeatureWhat it does
assist.suggest {relationId, cells?, maxCells?, record?}jevFor each candidate cell (default: from gaps.next), asks Jev a choice question over the relation's scale tokens, with a compact state from the two members' labels, descriptions and evidence. Returns {cell, token, probabilities, confidence} per cell; record: true stores them as proposed observations by actor {classifier, jev}.
gaps.next {rankBy: "uncertainty", relationId}jevRanks candidate cells by Jev uncertainty (1 − confidence).
proposals {relationId?}—Lists proposed observations awaiting confirmation.
assist.members {dimensionId, sourceText, sourceUri?}rigProposes new members from supplied text (README, interview notes, a competitor page), each with a verbatim excerpt and its character span. Never adds them; each comes with a ready member.propose payload.
assist.narrative {relationId?} / report {narrative: true}rigA short narrative of analyze.findings for the report.

Configuration: Jev uses https://api.typesafe.ai with jev-latest when TYPESAFE_JEV_API_KEY is set, otherwise OpenRouter with ~typesafe/jev-latest; override with CROSSMATRIX_JEV_BASE_URL, CROSSMATRIX_JEV_MODEL and CROSSMATRIX_JEV_TIMEOUT_SECS. Rig uses OpenRouter with CROSSMATRIX_RIG_MODEL (default openai/gpt-5-mini) and CROSSMATRIX_RIG_TIMEOUT_SECS. Calls are bounded (timeout, cells per call, token budget) and every response reports usage. Without the feature, opt-in or key, the query returns {ok: false, status: "assist_unavailable", reason, links}.

Agent skills

crossmatrix ships Agent Skills that teach an agent the method and common uses. Install them into a project (or --user) for one client or all:

sh
npx -y @matthew-cochran/crossmatrix skills install --target claude --project .crossmatrix-mcp skills install --target all --project .      # .claude/skills + .agents/skills

Targets: claude, codex, cursor, copilot, gemini, agents-md, all. A .crossmatrix-skills.json manifest records file hashes, so re-installs update only files you have not edited (--force overwrites them) and uninstall removes only unmodified files. The installer never edits MCP configuration; it prints the registration command instead (claude mcp add crossmatrix --scope user -- npx -y @matthew-cochran/crossmatrix).

SkillUse it for
crossmatrixthe method: Configuration / Dimensions / State, observation-only writes, the driver loop, scoped reads, .crossmatrix/
crossmatrix-hoqa classic House of Quality: weighted needs × characteristics, roof, technical importance, targets
crossmatrix-jtbdjobs to be done × user segments × journeys, joined by a contraction
crossmatrix-competitiveneeds × competitors benchmarking and gaps worth winning
crossmatrix-test-coveragerequirements/journeys × tests; orphans are untested requirements
crossmatrix-riskfailure modes × components/requirements (pairs with fmeca)
crossmatrix-prioritizedeliverables × value drivers → a ranked list for a planner (pairs with cpm)
crossmatrix-reviewcheck, conflicts, stale, the report and a sign-off checklist

Using it with Praxec

This is an MCP tool used by Praxec packs. The easiest way to get it — and a workflow pack that uses it — up and running is the one-command setup:

bash
curl -fsSL https://raw.githubusercontent.com/praxec/packs/main/setup.sh | bash

See the pack registry for this tool's provider coordinates (container image / release binary) and which packs depend on it.

Releasing

Maintainers: see docs/releasing.md (version bump, dev → main, tag, scripts/npm-release.sh, crates.io, rollback).

License

Apache-2.0.

来源:README.md,提交 3555966

工具

0
SourceWeft 曾在隔离沙箱中以无凭据方式启动该软件包一次,以列出其工具,但未能完成:该软件包类型无法在沙箱中运行。

版本历史

4
  1. v0.3.4最新Oct 22, 2026
  2. v0.3.3Oct 20, 2026
  3. v0.3.2Oct 16, 2026
  4. v0.3.1Oct 13, 2026

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