Zelinqa MCP

io.github.Zelinqa由 GitHub 帳號 Zelinqa 發布v1.0.1更新於 Oct 24, 2026

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

概覽

AI 產生的概覽

讓助理執行在 Zelinqa 中定義的目標導向對話:開始對話、傳入回覆、取得下一個問題並記錄結果。

可以做什麼
  • 開始或恢復指定名稱的對話,回傳第一個或待回答的問題
  • 記錄使用者回覆並回傳下一個問題,沒有回覆時僅重新顯示待答問題
  • 在不消耗輪次的情況下加入脈絡,或寫入已確認的資料與目標覆寫
  • 重新整理進度與待答問題,並記錄觀察到的業務結果
  • 釋放本機對話代碼
適用情境
適用於助理必須先詢問再決策的情境,例如訪談、潛在客戶資格判斷、方向引導、分流或推薦,且問題應來自已發布的 Zelinqa 網域而非臨時生成。
執行需求
以 uvx 執行的本機程序,需要 Python 3.11+ 與 uv。需要一個在 Zelinqa Studio 中為某個已發布網域建立的執行階段 API 金鑰(免費 Developer 版帳號即可),透過環境變數 ZELINQA_API_KEY 提供。選用變數可設定基底網址、逾時、重試與工作階段續接。需要連線至 Zelinqa API 的網路。
安裝前請注意
需要機密 ZELINQA_API_KEY,且僅限一個已發布網域。部分呼叫會建立工作階段並記錄回饋,建議保留主機的工具核准政策。對話名稱僅在程序內有效,重新啟動後續接需由主機在模型之外保存 API 工作階段 ID。forget 工具只釋放本機代碼,不會刪除 API 資料。達到輪次上限並不代表目標已達成。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Zelinqa MCP,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[Zelinqa MCP]

[PyPI version] [CI] [Python 3.11+] [MCP registry name] [License Apache-2.0]

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.

[An MCP host calls the zelinqa-mcp server over stdio; the server calls the Zelinqa API with the Python SDK and returns question text, choice labels and progress.]

Fewer tokens, deterministic, explainable

[70 percent fewer tokens, measured on 700+ conversations; deterministic: the same state returns the same question and choosing never calls a model; explainable: every question says what it collects and progress is reported per dimension.]

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

[Without Zelinqa, the model generates every question and decides with gaps. With Zelinqa, the engine runs the questioning phase from the published domain and the model decides once, with a complete typed state.]

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.

[Install in Cursor]   [Install in VS Code]

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 CodeClaude Desktop · Cursor · Windsurf
bash
claude mcp add zelinqa \  -e ZELINQA_API_KEY=YOUR_RUNTIME_API_KEY \  -- uvx zelinqa-mcp
json
{  "mcpServers": {    "zelinqa": {      "command": "uvx",      "args": ["zelinqa-mcp"],      "env": {        "ZELINQA_API_KEY": "YOUR_RUNTIME_API_KEY"      }    }  }}
Codex (~/.codex/config.toml)From a checkout
toml
[mcp_servers.zelinqa]command = "uvx"args = ["zelinqa-mcp"]env = { ZELINQA_API_KEY = "YOUR_RUNTIME_API_KEY" }
bash
git clone https://github.com/Zelinqa/zelinqa-mcp.gitcd zelinqa-mcpuv sync --group dev --lockeduv 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.

text
▶ 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.

來源:README.md,提交 98537b8

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

2
  1. v1.0.1最新Sep 29, 2026
  2. v1.0.0Sep 28, 2026

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