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

Concord Engine

作者:harsh-chandak版本 0.3.2i★ –i在你的电脑上运行
注册名称io.github.harsh-chandak/concord-engine

安装

概览

作者提供的说明(英文原文)

Scale parallelism. Preserve alignment. A fleet of coding agents builds one task in parallel against

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: 文档、表格与办公

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)。
  • 需要你自己填写: CONCORD_ENGINE_DIR

你需要

  • npm已安装 Node.js(用于 npx 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": {
    "concord-engine": {
      "command": "npx",
      "args": [
        "-y",
        "concord-engine"
      ],
      "env": {
        "CONCORD_ENGINE_DIR": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add concord-engine --env CONCORD_ENGINE_DIR=your-value -- npx -y concord-engine

运行前请先填写空着的值。

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": {
    "concord-engine": {
      "command": "npx",
      "args": [
        "-y",
        "concord-engine"
      ],
      "env": {
        "CONCORD_ENGINE_DIR": "your-value"
      }
    }
  }
}

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": {
    "concord-engine": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "concord-engine"
      ],
      "env": {
        "CONCORD_ENGINE_DIR": "your-value"
      }
    }
  }
}

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。

需要你填写的值

  • CONCORD_ENGINE_DIR env
    Where the decision log lives. Defaults to .concord-engine in the working directory. Commit it — the log is the shared contract between your agents.

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 harsh-chandak 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“文档、表格与办公”中的其他服务器比较i

  • 星标数多于此分类中其他 2197 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2197 个服务器的 69% 更新
  • 基础检查结果等于或优于此分类中其他 2197 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

Concord Engine 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(0.3.2)于15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 Node.js。

有什么可以替代它?

同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

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

Agent-Native Calendar

作者:BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

在云端运行★ 7,620MIT2个月前更新
安装

Excel MCP Server

作者:haris-musa

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

在你的电脑上运行★ 4,276MIT6天前更新
安装

MCP Server for Excel

作者:sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

在你的电脑上运行★ 847MIT4天前更新
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。

Concord Engine

Scale parallelism. Preserve alignment.

Describe a task. A fleet of agents builds it. They come back with work that is finished, tested and documented — and that agrees with itself, because none of them was allowed to contradict a decision another had already made.

Parallel agents don't scale past the human in the middle. You run five to go faster, four of them are right, the product is broken, and the only thing that catches it is you — reading everything, holding the whole picture, re-explaining choices that were already settled.

That isn't a prompting problem. Your agents have memory and they have verification, and neither answers the question that actually breaks a parallel run:

Did these two agents just settle the same question differently?

Concord Engine answers it by comparison, never by a model, and refuses the second answer at the moment it is written.

Recorded, not drawn. brag/record.mjs runs the real CLI and captures its output verbatim; brag/video.html only renders what was captured. The loop shows the refusal arc — the full run also writes the contract, binds it and briefs four workers first.

What a decision is

This is the part that gets undersold. A "decision" is not a variable name. It is any question two agents could answer differently and both be reasonable — and the cost is never the question itself, it's that nothing goes red.

KindReal examples
conventionmoney is integer minor units, never a float · timestamps are UTC ISO-8601 strings · pagination is cursor-based · every non-2xx body is {"error":" "} · retries are idempotent and capped at 3 · migrations ship in two reversible stages
api-contractPOST /api/orders returns 201, not 200 · tenant scoping lives in the path, not a header
enumorder status is `pending\paid\shipped · roles are owner\admin\member` · webhook events are a closed set
schemaid is a uuid and not null · amount_cents is an integer · soft deletes use deleted_at, not a boolean
namingthe identifier is user_id · the destination field is url, not target

Four agents implementing four reasonable answers to "what does an error body look like" produce four green test suites and one broken product. That is the whole category, and it is much wider than route paths.

The failure it stops

A refunds feature, split across a backend worker and a client worker. The backend settles the error shape. The client, working in parallel and with no visibility into the backend's files, reaches a different answer:

$ concord-engine decide --unit client --kind convention \

--subject "error response body shape" \ --value 'every non-2xx body is {"code":" ","detail":" "}' --as client

refused this contradicts a decision already in force. d-003 api (lead): error response body shape = every non-2xx body is {"error":" "} because: the client shows it to a person yours: every non-2xx body is {"code":" ","detail":" "}

Adopt the existing value, or supersede it deliberately: --supersedes d-003 --layer pm (an override, recorded as one) --force (record the disagreement for check to surface)

Verbatim from the recording above.

The agent is stopped at the moment it tries to disagree, and told what is in force, who decided it, why, and the two legitimate ways out. Not at integration. Not by you.

Three ways to run it

As a skill, which is how most people will use it. Describe the task; the agent runs the whole loop — authors the contract, binds it, briefs each worker, fans out, gates every decision, runs the acceptance checks, writes the design doc.

/concord-engine:concord-engine add refunds across the API, the client and the schema

/concord-engine:concord-engine migrate us off the legacy auth tables, five workers /concord-engine:concord-engine rename the tenant concept to workspace everywhere

Nothing about the task has to be small, and nothing has to be a route.

As an MCP server, so an agent already mid-task can reach the gate without being handed a workflow. Twelve tools: write_contract, bind_contract, brief_unit, fleet_plan, run_acceptance, generate_docs, cost_report, plus record_decision, binding_decisions, open_conflicts, record_attempt, status.

As a CLI, for humans and for CI. concord-engine check exits non-zero when anything contradicts, which is a one-line pipeline step.

Why this isn't another memory tool

ToolAnswersDoesn't answer
Handoff / memory tools"what did the last agent know?""do these two agree?"
Orchestrator verification"did this worker do its task?""do these two agree?"
Edit-conflict detection"did two agents touch one file?""do these two agree?"

And the obvious way to answer it — store decisions as prose, ask a model whether two of them conflict — is slow, costs a call per check, and is wrong often enough that people stop trusting it. A coordination layer nobody trusts is worse than none, because it adds latency and false alarms to a workflow that had neither.

Concord Engine decides agreement by comparison, never by a model. Decisions are typed and narrow, so a contradiction is a comparison: same subject, different value. No API call exists anywhere in the decision path — there's a test that fails if any file in that path can reach outside the process, and a second one that fails if any file in the package, anywhere, calls a model.

The loop

The gate above is one organ. v0.2 is the body around it: you describe a task, and the fleet that builds it is bound to one set of decisions from before the first line of code.

  describe a task

| [1] CONTRACT the agent authors JSON to a published schema; | the package validates it and stores it v [2] BIND the contract's decisions enter the log at PM layer, | binding before any code exists v [3] BRIEF one brief per unit: its slice, the decisions it must | honour, what it may not decide, how it will be judged v [4] FAN OUT the host spawns one worker per unit, each getting a | brief and nothing else v [5] GATE a worker that tries to decide something contradictory | is refused, told what is in force and who may override v [6] ACCEPT every acceptance criterion carries a command; the run | is not done until all of them exit 0 v [7] DOCS the design doc is generated from the decision log — | what was decided, by whom, and why v [8] COST what the fan-out sent, in bytes

concord-engine spec --schema              # the contract shape, as JSON Schema

concord-engine spec --from contract.json # validate and store it concord-engine bind --contract add-refunds concord-engine fleet --contract add-refunds # every brief, as JSON concord-engine brief --contract add-refunds api # one worker's brief concord-engine accept --contract add-refunds # run every check concord-engine docs --contract add-refunds concord-engine cost --contract add-refunds

Every loop command takes --contract. The MCP server exposes the same set as write_contract, bind_contract, brief_unit, fleet_plan, run_acceptance, generate_docs and cost_report.

The contract

One JSON document. The agent writes it; the package decides whether it holds.

openSubjects is the part people skip and shouldn't. Naming a thing before anyone decides it is what stops two workers inventing two different names for it — see Honest limits for the run where that went wrong.

{

"id": "add-refunds", "goal": "one sentence a reviewer can judge the result against", "scope": { "in": ["..."], "out": ["..."] }, "decisions": [ // binding from t=0, at PM layer { "kind": "api-contract", "subject": "refund endpoint", "value": { "method": "POST", "path": "/api/refunds", "status": 201 }, "rationale": "why this and not the alternative" } ], "openSubjects": [ // known to need deciding, not yet decided { "kind": "convention", "subject": "error response body shape", "note": "the server and the client both serialise this" } ], "units": [ // one worker each { "id": "api", "goal": "...", "files": ["src/api/**"], "mayDecide": ["convention"], // everything else must be requested "dependsOn": [] } ], "acceptance": [ { "id": "a1", "statement": "refunds endpoint returns 201", "check": "npm test -- refunds", "unit": "api" } ] }

Validation is not a formality. A contract is rejected when two of its own decisions contradict each other, when a unit depends on one that doesn't exist, when the dependency graph has a cycle, when a unit has no acceptance criterion, or when a criterion has no command. All of it in one pass, because fixing one error per round trip is the expensive way to find four:

$ concord-engine spec --from contract.json

concord-engine: contract is not valid:

  • unit "api" depends on "ui", which is not a unit in this contract
  • acceptance[a1] has no check — a criterion without a command is a wish

bind then puts the contract's decisions into the log at PM layer. If one of them contradicts a decision already live, binding refuses — a new contract quietly overriding decisions in force is the exact failure this tool exists to prevent.

What one worker gets

A brief, and not the conversation. This is the actual brief the unit that wrote this file was given. Verbatim, abridged only where marked:

$ concord-engine brief --contract concord-engine-v2 readme

You are one worker on "concord-engine-v2". Your unit is "readme".

GOAL Rewrite README.md around the loop without losing the v0.1 pitch that the gate is the product.

FILES YOU OWN README.md Do not edit files outside this list. Another worker owns them.

DECISIONS ALREADY IN FORCE — these are not suggestions

  • [convention] model calls inside the package = no file in the package may call a model or open a network connection; enforced by a test (the one defensible sentence is that agreement is decided by comparison, never by a model — if authoring moves inside the package that stops being true)
  • [naming] cli flag for selecting a contract = --contract (every loop command takes it, so it has to be the same word everywhere) ... 3 more decisions in force

WHAT YOU MAY DECIDE nothing — you write code and decide nothing

WHAT YOU MUST NOT DECIDE ALONE naming, convention, api-contract, enum, schema

RECORD A DECISION LIKE THIS — the flags are what enforce the two lists above concord-engine decide --contract concord-engine-v2 --unit readme \ --kind --subject " " --value ' ' --as readme --rationale " "

Omitting --unit skips the check on what you may decide. Use the MCP tool record_decision if you have it; it gates the same way. A refusal means a decision already covers this: adopt the existing value. Do not work around it, and do not --force it.

DONE MEANS [a-readme] the README covers the loop and keeps the gate pitch $ test -f README.md && grep -q 'spec --schema' README.md && grep -q 'refus' README.md && grep -q -i 'estimate' README.md

fleet prints all of them at once,

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