原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Mneme Decision MCP

作者:MnemeHQ版本 0.10.0i★ –i在你的电脑上运行
注册名称io.github.MnemeHQ/mneme

安装

概览

作者提供的说明(英文原文)

Local MCP server for architectural decisions, traceability, and non-authoritative proposals.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "mneme": {
      "command": "uvx",
      "args": [
        "mneme-hq",
        "mneme",
        "decision-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add mneme -- uvx mneme-hq mneme decision-mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "mneme": {
      "command": "uvx",
      "args": [
        "mneme-hq",
        "mneme",
        "decision-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "mneme": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mneme-hq",
        "mneme",
        "decision-mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 MnemeHQ 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32700 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32700 个服务器的 57% 更新
  • 基础检查结果等于或优于此分类中其他 32700 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Mneme Decision MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.10.0)于30天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Agent Data Tools: Utilities

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

Agent Data Tools: Utilities

作者:Nutshell2000

103 tools: JSON repair, CSV, hashes, cron, dates, units, validators. 25 free calls.

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Mneme HQ

Mneme is an open decision and control layer for agentic software development.

It turns durable engineering decisions into agent context, deterministic enforcement, and inspectable enforcement results across AI coding agents, repositories, and CI workflows. Architecture is the first supported decision domain: Mneme prevents architectural drift by turning architectural decisions and ADRs into deterministic guardrails across coding agents, repository mutations, generated rules, and CI gates.

Where is your architecture actually enforced? Run the Architecture Audit to see which decisions are protected, which can become deterministic guardrails, and which still depend on someone remembering the rules. Try it →

Mneme is the decision layer behind that drift-prevention mechanism. It keeps recorded engineering decisions active as AI coding systems propose and modify code, instead of leaving ADRs as passive documentation.

Solid surfaces ship today; dashed surfaces are planned. Support levels per integration: integrations matrix.

Current phase: Layer 1 validation. Retrieval, enforcement, and benchmark semantics are governed by the accepted architecture and freeze record. See Current Phase before changing core behavior.

What Mneme does

Mneme separates architectural guidance from deterministic enforcement:

  • Records architectural decisions in a structured, auditable decision corpus.
  • Retrieves relevant decisions when an agent or model needs architectural guidance.
  • Enforces governed rules deterministically under explicit applicability semantics.
  • Integrates at the earliest reliable boundary exposed by each coding workflow.
  • Audits bypassable mutation paths where pre-change blocking is not technically available.
  • Runs in CI as a final deterministic gate before incompatible changes are accepted.

The same input and governed decision state produce the same enforcement result. Mneme does not depend on an LLM judge for its core allow/warn/fail decisions.

Mneme is not a general-purpose vector store, conversational memory system, autonomous coding agent, or deployment observability platform.

Install

Requires Python 3.11+.

pip install mneme-hq

Verify the CLI:

mneme --help

For repository development:

git clone https://github.com/MnemeHQ/mneme.git

cd mneme pip install -e ".[dev]"

Decision MCP

Mneme exposes the Decision Index over a local MCP server so MCP-capable clients can propose candidate architectural decisions and query decision state without gaining authority to change that state.

Install the optional MCP dependency:

pip install "mneme-hq[mcp]"

Start the local stdio server. Canonical reads come from the persisted Decision Index in .mneme/project_memory.json by default; the proposal store remains separate.

mneme decision-mcp

Use --memory to select another project memory file. The file must contain a valid authoritative decision_index section; MCP fails closed rather than reconstructing authority from the compatibility decisions[] snapshot.

mneme decision-mcp --memory path/to/project_memory.json

Memory created by mneme init or mneme setup already carries an empty decision_index section and needs no migration. An older file with no decision_index section yet makes MCP stop with an error that tells you to migrate. Preview the migration first. It writes nothing and lists the visible effects: non-active decisions leave Layer 1, and legacy rule/anti_pattern items are migrated once.

mneme decision-index migrate --memory path/to/project_memory.json

Then apply exactly that migration:

mneme decision-index migrate --memory path/to/project_memory.json --apply

Migration is lossless or it refuses. There is no force or repair mode. Memory containing legacy decision metadata that the canonical index cannot represent, such as EventCatalog-imported decisions, stays on the section-less path and is not migrated.

--adr-dir is now optional validation input only. Mneme still validates and precedence-resolves that corpus before startup, but ADRs do not become a second MCP authority source.

mneme decision-mcp --memory path/to/project_memory.json --adr-dir path/to/adrs

The MCP surface is intentionally frozen to six tools:

  • decision.propose
  • decision.propose_batch
  • decision.get
  • decision.search
  • decision.applicable_to
  • decision.trace

Proposal tools create non-authoritative proposals only. Read tools query proposal and canonical decision state. MCP deliberately exposes no accept, reject, activate, supersede, exception, bypass, or trusted-evidence authority.

Human authority remains explicit through mneme decision proposals | show | accept | reject. Accepting a proposal materializes a canonical decision; it does not activate protection or run the Architecture Audit.

See ADR-027 and the v0.9.0 release notes for the authority boundary and release contract.

Architecture Audit

See where your architecture is actually protected — and where it still depends on people remembering the rules.

Mneme audits your repository and shows which architectural decisions are:

  • Protected — already enforced mechanically
  • Mneme-ready — can be turned into a deterministic guardrail
  • Requires modelling — important, but not yet safe to automate
  • Guidance — useful context, but not something that should be enforced

Run an audit:

mneme audit --memory .mneme/project_memory.json --repo-root .

For a Mneme-ready decision, validate the proposed protection before enabling it:

mneme protect validate <decision-id> --memory .mneme/project_memory.json

Then explicitly activate it:

mneme protect activate <decision-id> --memory .mneme/project_memory.json

Mneme only reports a decision as Protected after it can verify that real enforcement is in place. The full activation contract is documented in Protection Activation.

Try the Architecture Audit →

60-second enforcement example

Initialize a project-local decision corpus:

mneme init

Record one architectural decision:

mneme add_decision \

--memory .mneme/project_memory.json \ --id config-format \ --decision "Use JSON for configuration files" \ --scope config \ --constraint "Use JSON only" \ --anti-pattern "Do not use YAML"

Create a proposed input that violates it:

python -c "import pathlib; pathlib.Path('prompt.txt').write_text('Set up a new YAML config file', encoding='utf-8')"

Run the deterministic check:

mneme check \

--memory .mneme/project_memory.json \ --input prompt.txt \ --query configuration

In strict mode, the prohibited YAML proposal returns a FAIL verdict and exit code 2. A compliant JSON proposal returns PASS and exit code 0.

The CLI is the common enforcement surface. Agent integrations translate their native events into the same Mneme decision and enforcement model.

For a non-authoritative preview of which canonical decisions would apply to caller-asserted context labels, add an opt-in, repeatable --applicability-preview to mneme check:

mneme check --memory .mneme/project_memory.json --input prompt.txt --query configuration --applicability-preview platform:windows

The preview prints only on stderr, independently of the normal check result. It does not trust the supplied labels, exclude decisions, change enforcement, or change stdout, JSON mneme.check/v1, hook behavior, or exit codes. Section-less memory or a preview computation error reports PREVIEW UNAVAILABLE on stderr; it does not migrate memory or weaken enforcement. This preview is not a security control.

Setup mode (no enforcement)

mneme setup initializes Mneme in a repository without changing how the team works: it creates or detects project memory, detects supported agent environments, and reports protection readiness — all without enabling any blocking enforcement. Setup never turns warn/observe behavior into blocking behavior; activation of preventive enforcement is always a separate, explicit decision.

mneme setup

Optionally record an opaque Architecture Audit reference so the setup can be attributed back to a saved Audit baseline:

mneme setup --audit-ref <reference>

Setup is idempotent: rerunning it against an existing Mneme project leaves valid configuration untouched.

How it works

Architectural decisions / ADRs

| v structured decision corpus | +-----+--------------------+ | | v v relevant guidance deterministic enforcement retrieval + applicability checks | | +------------+-------------+ | v workflow-specific boundary | +------------+-------------+ | | | pre-change post-change CI hooks audit gate

Mneme applies governance at the earliest reliable boundary a workflow exposes:

  1. Before generation when architectural context can be injected into the model call.
  2. Before supported file mutations when an agent exposes a blocking pre-tool hook.
  3. After bypassable mutations through bounded working-tree audits where shell/script writes cannot be inspected safely before execution.
  4. Before merge through CLI-based CI gates.

These boundaries are complementary. An integration only claims the surfaces that have been implemented and validated for that harness.

Retrieval is not enforcement

Decision retrieval answers: which architectural decisions are useful as guidance for this task?

Enforcement answers: does the proposed change violate a governed rule that applies here?

Those concerns are intentionally separated. See ADR-017, ADR-019, and ADR-020.

Supported surfaces

The authoritative support matrix lives in docs/integrations/README.md. The labels below are evidence levels, not interchangeable marketing terms.

Support levelSurface
Native integrationClaude Code
Native integrationClaude Agent SDK
Native integrationGoogle Antigravity
Native integrationCodex CLI
Native integrationKiro CLI 3.0 / v3
Validated compatibilityPaperclip — CLI and ACP transports, no adapter required
Rules exportCursor

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