Progi

Name: Progi
Author: zseta

by zsetaversion 0.3.2i★ –iRuns on your computer

Registry nameio.github.zseta/progi

Install

Overview

Description from the maker (original English)

MCP-native workflow engine: teach agents your processes once, they execute them consistently.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: PROGI_DB_PATH

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "progi": {
      "command": "uvx",
      "args": [
        "progi"
      ],
      "env": {
        "PROGI_DB_PATH": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add progi --env PROGI_DB_PATH=your-value -- uvx progi

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "progi": {
      "command": "uvx",
      "args": [
        "progi"
      ],
      "env": {
        "PROGI_DB_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "progi": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "progi"
      ],
      "env": {
        "PROGI_DB_PATH": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

PROGI_DB_PATH env
Custom path for the Progi SQLite database file

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account zseta, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32433 servers in this category
Published to the registry more recently than 13% of the other 32433 servers in this category
Basic checks equal to or better than 100% of the other 32433 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Progi safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.2) reached the registry 5 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago

Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday

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Symantec Cloud DLP AIops

by AIops-tools

Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.

Runs on your computerUpdated today

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Progi - MCP-native Workflow Engine

Progi teaches your agent how you like to get things done. So you can do your best work without re-explaining your process or losing context between sessions.

Get started

Add Progi to your MCP client config (GH Copilot / Cursor / Claude Code / etc):

"mcpServers": { "progi": { "command": "uvx", "args": ["progi"] } } }

Progi Monitoring starts automatically at http://127.0.0.1:8000.

If you want to start Monitoring on a different port:

"mcpServers": { "progi": { "command": "uvx", "args": ["progi"], "env": { "PROGI_WEB_PORT": "8080" } } } }

How it works

1. Describe your workflow

*"Hey Progi, help me create workflow for creating integrations, reviewing code, and publishing PRs."*

Describe your process in plain language. You can be detailed or just provide a rough idea. Progi stores it as a structured workflow with per-step playbooks.

2. Run tasks, stay in the loop

*"Hey Progi, start a new task, we need to review a new docs PR in the repo."* Your agent loads the workflow, works through each step using your playbooks, and loops you in at critical checkpoints to review output.

3. Monitor progress

Progi Monitoring gives you a live view of every running and completed task — status, progress, and the full output history across all your workflows.

4. Optimize as you go

Tweak playbooks in Progi Monitoring between runs. Because workflows live in a database and survive context resets, every future task picks up your changes automatically — your process gets sharper with each iteration.

MCP Tools

Work loop

Tool	Description
`create_task`	Create a new task under a given workflow (status `todo`); returns a preview of its first step
`list_tasks`	List tasks, optionally filtered by status and/or workflow
`start_or_continue_task`	Main work-loop entry point — starts or resumes a task and returns the current step's playbook, input data, and output spec
`update_progress_notes`	Overwrite a task's progress notes (mid-step save point)
`finish_step`	Mark the current step complete, store its output, and advance to the next step (or mark done)

Workflow authoring

Tool	Description
`get_process_skeleton_prompt`	Return the Pass 1 system prompt for turning a plain-language description into a structured workflow skeleton
`get_playbook_authoring_prompt`	Return the Pass 2 system prompt for authoring a step's playbook (injects workflow context)
`save_workflow`	Persist a new workflow, its steps, and playbooks
`list_workflows`	Return all workflows with their ordered steps

Authoring is two passes: Pass 1 turns a plain-language description into a structured skeleton; Pass 2 authors each step's playbook. save_workflow persists both.

Configuration

Variable	Default	Purpose
`PROGI_DB_PATH`	OS data dir (`platformdirs`)	SQLite file location
`PROGI_WEB_HOST`	`127.0.0.1`	Web UI bind host
`PROGI_WEB_PORT`	`8000`	Web UI port
`PROGI_NO_WEB`	`0`	Set to `1` to disable the web UI

Run modes: uvx progi (MCP + web UI), uvx progi --no-web (MCP only), uvx progi-web (web UI only).

Use an absolute path for PROGI_DB_PATH

Progi

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Symantec Cloud DLP AIops

README from the maker

Progi - MCP-native Workflow Engine

Get started

How it works

MCP Tools

Work loop

Workflow authoring

Configuration