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Code execution · MCP server

Prolog Reasoner: MCP server, setup and security

Prolog Reasoner is an open-source MCP server published on GitHub that lets an AI agent execute SWI-Prolog programs using constraints negation as failure and recursion. Its repository has 12 stars and its last commit is from May 1, 2026 and it is licensed under MIT.

Score
49/100
Adoption (stars) 11/40
Maintenance 18/30
Framework (licence, registry, official) 20/30
Last commit 6 months agoSystem access

What Prolog Reasoner does

According to its repository: “SWI-Prolog execution for LLMs with CLP(FD), negation as failure and recursion.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Prolog Reasoner is listed under Code execution, a category of 32 servers in the directory, where it ranks #27 by stars.

Topics declared by the repository: anthropic, claude, logic-programming, prolog, python, reasoning.

Installing and connecting Prolog Reasoner

Distribution modes declared in the official MCP registry:

  • PyPI package (Python, started with uvx or pip)

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: Python. Listed systems: macOS, Windows, Linux.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

Points found for Prolog Reasoner:

  • System access: the Code execution category gives the agent control over files, a terminal, code or a browser. A booby-trapped instruction in content the agent reads (prompt injection) can then turn into an action.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on April 14, 2026, the rikarazome/prolog-reasoner repository has 12 stars and 1 forks, with 0 open issues. It has more stars than 29% of the servers in the directory. Last change 6 months ago. Version published in the registry: 0.2.1 (April 17, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

Container useContainer use : 4.1K4.1KMATLAB MCP ServerMATLAB MCP Server : 1.7K1.7KLLM SandboxLLM Sandbox : 1.1K1.1KTidewave PhoenixTidewave Phoenix : 858858Tidewave RailsTidewave Rails : 476476SuperserveSuperserve : 466466IPhone UseIPhone Use : 345345OrcaReplayOrcaReplay : 281281Prolog ReasonerProlog Reasoner : 1212
GitHub stars of the most followed servers in the category (log scale); Prolog Reasoner in orange. Checked October 25, 2026.

Verdict

Prolog Reasoner is still a modest project: read its code and compare it with the alternatives before using it.

Strengths

  • Listed in the official MCP registry
  • Permissive licence (MIT)

Limitations

  • Few visible users

Avoid if…

  • You cannot isolate the agent (sandbox, container)

Frequently asked questions

How do I install Prolog Reasoner?

Prolog Reasoner is distributed as PyPI package (Python, started with uvx or pip). Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of rikarazome/prolog-reasoner.

Is Prolog Reasoner free?

The code is published under the MIT licence and can be used free of charge.

Is Prolog Reasoner safe?

Points to watch: system access. Give it minimum rights and approve sensitive actions.

Is it an official server?

Nothing says so: it is a project published by rikarazome on GitHub. Check who maintains it before giving it access.

What are the alternatives to Prolog Reasoner?

In the same category: Container use, LLM Sandbox, Tidewave Phoenix, and Superserve. Container use and LLM Sandbox score higher on our grid.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score