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Zelinqa MCP

by Zelinqaversion 1.0.1i★ –iRuns on your computer
Registry nameio.github.Zelinqa/zelinqa-mcp

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other
  • You need to fill in: ZELINQA_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: ZELINQA_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

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

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

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

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Zelinqa, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32558 servers in this category
  • Published to the registry more recently than 51% of the other 32558 servers in this category
  • Basic checks equal to or better than 100% of the other 32558 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Zelinqa MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: ZELINQA_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.1) reached the registry 38 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, FactLot

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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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