Federated AI Commons MCP Server

by toby-self Your server? Claim it

local only

Federated AI Commons runs on your own machine — the client starts it, so there is no endpoint to ping. 89 installs a week from pypi. Last commit 14 Jul 2026.

MCP server for a federated AI-commons governance simulation with a verified compliance oracle.

Installs per day peak 31 · avg 14 · -26% w/w

a month agotoday

Installs / week

pypi · federated-ai-commons-mcp

Stars

0 open issues

14 Jul 2026

Last commit

from GitHub

Apache-2.0

License

Python

What the code does

We read the source, 3 d ago · rules 995398eba69f

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

File ships in the package but is absent from the source [пакет] federated_ai_commons_mcp_server.py:1, [пакет] federated_ai_commons_model.py:1

этот файл ставится пользователю, но в репозитории его нет

Runs an external command asymptotic_ethics_mcp_server.py:301, [пакет] federated_ai_commons_mcp_server.py:287

    result = subprocess.run(

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add federated-ai-commons -- uvx federated-ai-commons-mcp

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "federated-ai-commons": {
      "command": "uvx",
      "args": [
        "federated-ai-commons-mcp"
      ]
    }
  }
}

~/.codex/config.toml

[mcp_servers.federated-ai-commons]
command = "uvx"
args = ["federated-ai-commons-mcp"]

.cursor/mcp.json

{
  "mcpServers": {
    "federated-ai-commons": {
      "command": "uvx",
      "args": [
        "federated-ai-commons-mcp"
      ]
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "federated-ai-commons": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "federated-ai-commons-mcp"
      ]
    }
  }
}

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answering

Federated AI Commons — questions

Answers built from our own checks of this server.

Why is there no uptime for Federated AI Commons?

Federated AI Commons runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package federated-ai-commons-mcp was installed 89 times last week.

How do I connect Federated AI Commons?

Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It runs locally, so the command pulls federated-ai-commons-mcp straight from pypi; nothing to host, nothing to sign up for.

How many people use Federated AI Commons?

The pypi package federated-ai-commons-mcp was installed 89 times in the last week. Week over week that is -26%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.

Is Federated AI Commons open source?

Yes — it is published under the Apache-2.0 licence, written in Python and 0 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.