
Zelinqa MCP
io.github.ZelinqaPublished by GitHub account Zelinqav1.0.1Updated Oct 24, 2026
Goal-oriented conversations and next-question selection through the Zelinqa API.
Overview
Lets an assistant run a guided, goal-oriented conversation defined in Zelinqa: start it, pass replies, get the next question, record the outcome.
- What you can do
- Start or recover a named conversation and get its first or pending question
- Record a reply and receive the next question, or redisplay the pending one
- Add context or apply confirmed data and objective overrides without consuming a turn
- Refresh progress and the pending question, and record an observed business result
- Free the local conversation handle
- When to use it
- Useful when an assistant must ask before it decides: interviews, lead qualification, orientation, triage or recommendations, where the questions should come from a published Zelinqa domain instead of being improvised.
- Requirements
- Local process run with uvx, needing Python 3.11+ and uv. A runtime API key for one published domain, created in Zelinqa Studio (a free Developer edition account suffices), supplied as the ZELINQA_API_KEY environment variable. Optional variables set the base URL, timeout, retries and session resume. Network access to the Zelinqa API.
Installation
In SourceWeft
- Open Zelinqa MCP in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
[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.
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.
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
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.
zelinqa-mcp --advanced swaps the business tools for six low-level ones that expose API identifiers and full state. See docs/operations.md.
Configuration
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_statusand 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.
Source: README.md at commit 98537b8
Tools
0Version history
2- v1.0.1LatestSep 29, 2026
- v1.0.0Sep 28, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts