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。
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Zelinqa MCP

作者:Zelinqa版本 1.0.1i★ –i在你的电脑上运行
注册名称io.github.Zelinqa/zelinqa-mcp

安装

概览

作者提供的说明(英文原文)

Goal-oriented conversations and next-question selection through the Zelinqa API.

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
  • 你需要填写:ZELINQA_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

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": {
    "zelinqa": {
      "command": "uvx",
      "args": [
        "zelinqa-mcp"
      ],
      "env": {
        "ZELINQA_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add zelinqa --env ZELINQA_API_KEY=your-value -- uvx zelinqa-mcp

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": {
    "zelinqa": {
      "command": "uvx",
      "args": [
        "zelinqa-mcp"
      ],
      "env": {
        "ZELINQA_API_KEY": "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": {
    "zelinqa": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "zelinqa-mcp"
      ],
      "env": {
        "ZELINQA_API_KEY": "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

  • ZELINQA_API_KEY 机密 必填 env
    Runtime key for a published Zelinqa domain, supplied by the host.

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 Zelinqa 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 32497 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32497 个服务器的 51% 更新
  • 基础检查结果等于或优于此分类中其他 32497 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

Zelinqa 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?

你需要填写:ZELINQA_API_KEY

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(1.0.1)于38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, Zoo MCP

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昨天更新
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Zoo MCP

作者:KittyCAD

An MCP server that provides access to the Zoo API for various CAD operations and tools.

在你的电脑上运行今天更新
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。

Install · Example · Tools · Configuration · Operations · Français


Your assistant handles the conversation. Zelinqa decides what to ask next. Describe once, in Zelinqa Studio, what a conversation must find out. This server gives any MCP host the tools to run that conversation: start it, pass each reply, get the next question, record the result. The model only ever sees question text, choice labels and a conversation name. Session, decision and state identifiers stay inside the server.

Fewer tokens, deterministic, explainable

The engine chooses the questions, so the model stops generating them and stops re-asking: fewer tokens for the same dialogue. The choice itself is a selection over your published domain, not a generation: the same state always yields the same question, and each decision carries what the question collects, the progress of every dimension and an explicit stop reason, so a conversation can be audited after the fact. Token figures: internal test bench, September 2026: more than 700 conversations replayed twice with the same assistant, alone then steered by the Zelinqa engine, with simulated respondents replayed identically on both sides. Protocol, figures and limits: read the test bench report. A scientific benchmark with shared data and code is planned before the end of 2026.

Why

Any assistant that has to ask before it decides, for an interview, a qualification, an orientation, a triage or a recommendation, improvises its questions and decides with gaps. With this server, the engine runs the questioning phase from your published domain and the model decides once, with a complete, typed state.

Install

You need Python 3.11+ with uv, and a runtime API key for a published domain, created in Zelinqa Studio. A free Developer edition account is enough.

Or add the server to your host by hand. The command is the same everywhere: uvx zelinqa-mcp, with the key in the host's secret environment.

Claude Code Claude Desktop · Cursor · Windsurf

claude mcp add zelinqa \

-e ZELINQA_API_KEY=YOUR_RUNTIME_API_KEY \ -- uvx zelinqa-mcp

{

"mcpServers": { "zelinqa": { "command": "uvx", "args": ["zelinqa-mcp"], "env": { "ZELINQA_API_KEY": "YOUR_RUNTIME_API_KEY" } } } }

Codex ( ~/.codex/config.toml ) From a checkout

[mcp_servers.zelinqa]

command = "uvx" args = ["zelinqa-mcp"] env = { ZELINQA_API_KEY = "YOUR_RUNTIME_API_KEY" }

git clone https://github.com/Zelinqa/zelinqa-mcp.git

cd zelinqa-mcp uv sync --group dev --locked uv run zelinqa-mcp --version

Ready-to-copy files for each host are in examples/. Keep your host's tool-approval policy: some calls create sessions and feedback.

A conversation in four tool calls

The model calls zelinqa_start, asks the returned question in its own words, passes the person's reply to zelinqa_next_question, and repeats until the engine stops. At the end it records what really happened.

▶ zelinqa_start           {"conversation": "lead-42"}

◀ ask · "Which budget range are you considering this year?" choices: Under €10k · €10k to €50k · Over €50k

▶ zelinqa_next_question {"conversation": "lead-42", "choice_labels": ["€10k to €50k"]} ◀ ask · "When would you like to start?" progress: budget covered · timeline not started

▶ zelinqa_next_question {"conversation": "lead-42", "user_text": "Next quarter, after the sales kickoff."} ◀ stop · objective achieved

▶ zelinqa_feedback {"conversation": "lead-42", "result": "success"}

Calling zelinqa_next_question without a reply only redisplays the pending question. When a CRM already knows an answer, zelinqa_adjust records it without asking. zelinqa_adjust and zelinqa_add_context can replace the pending question, for example when the information it asked for is now known: always ask the question they return. The full answering rules are in docs/operations.md.

Tools

ToolWhat it does
zelinqa_startStart or recover a named conversation and return its first or pending question
zelinqa_next_questionRecord the person's reply and return the next question; without a reply, redisplay the pending question without a new turn
zelinqa_add_contextAdd a context summary without asking a question
zelinqa_adjustApply confirmed data, dimension statuses or an objective override without consuming a turn
zelinqa_statusRefresh progress and the pending question
zelinqa_feedbackRecord an observed business result: success, partial or failure
zelinqa_forgetFree the local handle; does not delete API data

Results carry question text, ranks, choice labels, objective progress and counters; next-decision results add warnings, the stop reason and degraded-mode reasons. At max_turns the result has action: "stop" and stop_reason: "max_turns_reached", and later calls return the same stop. Reaching the turn limit is not proof that the objective was achieved.

Also availablePurpose
Resource zelinqa://guideThe same guide supplied as the server's instructions
Prompt zelinqa_integration_checkUser-selected integration test checklist
Skill zelinqaShort workflow for hosts that support skills; copy the directory into your host's skills folder

zelinqa-mcp --advanced swaps the business tools for six low-level ones that expose API identifiers and full state. See docs/operations.md.

Configuration

Environment variablePurpose
ZELINQA_API_KEYRequired runtime key, scoped to one published domain
ZELINQA_BASE_URLDefault https://api.zelinqa.ai
ZELINQA_TIMEOUT_SECONDSPer-attempt timeout, default 30 seconds
ZELINQA_MAX_RETRIESRetry count, default 2
ZELINQA_SESSION_IDOptional host-owned session to resume after restart
ZELINQA_CONVERSATIONLocal name of that resumed session; default conversation

Security and state

  • Transport is stdio, one isolated process per trusted host and user. HTTP hosting is disabled until authentication and session isolation exist. Logs go to stderr; stdout is reserved for MCP.
  • The server holds at most 128 named conversations in memory and never evicts one silently. Names are process-local: to survive a restart, the host keeps the API session id and injects the resume variables above, outside the model.
  • Calls that mutate the same conversation must be sequential; a simultaneous call is rejected rather than answered with stale state. After a conflict, call zelinqa_status and reconcile before answering again.

Details, retry semantics and the test suites: docs/operations.md. Vulnerability reports: SECURITY.md.

Related

  • zelinqa-sdk: the Python and TypeScript clients this server is built on, for applications that call the API directly.
  • docs.zelinqa.ai: concepts, Studio guide and API reference.

License

Apache-2.0. Release steps are in RELEASING.md.

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