Aggregators and gateways · MCP server
Humanizer ru (Vladimir-Human): MCP server, setup and security
Humanizer ru (Vladimir-Human) is an open-source MCP server that lets an AI agent detect and normalize machine generation traces in Russian language text. Its repository has 130 stars and its last commit is from October 21, 2026 and it is licensed under MIT.
| Adoption (stars) | 21/40 | |
|---|---|---|
| Maintenance | 30/30 | |
| Framework (licence, registry, official) | 20/30 |
What Humanizer ru (Vladimir-Human) does
According to its repository: “Detect and normalize traces of machine generation in Russian text, without authorship verdicts.”
An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. Humanizer ru (Vladimir-Human) is listed under Aggregators and gateways, a category of 141 servers in the directory, where it ranks #59 by stars.
Topics declared by the repository: humanizer, russian, agent-skills, claude-skill, russian-language, claude-code.
Installing and connecting Humanizer ru (Vladimir-Human)
Distribution modes declared in the official MCP registry:
- PyPI package (Python, started with
uvxorpip)
Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: Python. Listed systems: macOS, Windows, Linux.
Security: what to check
An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.
None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Humanizer ru (Vladimir-Human). That does not replace reading the code.
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 January 21, 2026, the Vladimir-Human/humanizer-ru repository has 130 stars and 12 forks, with 0 open issues. It has more stars than 71% of the servers in the directory. It received changes this month. Version published in the registry: 3.36.4 (September 13, 2026).
Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.
Verdict
Humanizer ru (Vladimir-Human) is a reasonable choice; check the points below before connecting it.
Strengths
- Active project: recent commit
- Listed in the official MCP registry
- Permissive licence (MIT)
Alternatives
- GitDiagram18.4K ★
- Mockserver monorepo5K ★
- Paperclip106.8K ★
- Basebalance.cloud — x402 RPC & MCP gateway7.5K ★
- AIHOT8.5K ★
- OpenWork MCP Gateway24.2K ★
Learn more
Frequently asked questions
How do I install Humanizer ru (Vladimir-Human)?
Humanizer ru (Vladimir-Human) 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 Vladimir-Human/humanizer-ru.
Is Humanizer ru (Vladimir-Human) free?
The code is published under the MIT licence and can be used free of charge.
Is Humanizer ru (Vladimir-Human) safe?
No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.
Is it an official server?
Nothing says so: it is a project published by Vladimir-Human on GitHub. Check who maintains it before giving it access.
What are the alternatives to Humanizer ru (Vladimir-Human)?
In the same category: GitDiagram, Mockserver monorepo, Paperclip, and Basebalance.cloud — x402 RPC & MCP gateway. GitDiagram and Mockserver monorepo 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