Spec Driven Development
by formulahendry
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Runs on your computer★ 440MITUpdated 14 months ago
Install
MaskFlow PII proxy
Overview
Description from the maker (original English)
Mask PII in outbound MCP tool-call arguments, unmask the results. Indian identifiers included.
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).
- The registry lists no key to fill in.
You need
- PyPIPython’s uv installed (for the uvx command)
Which app do you use?
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": {
"maskflow": {
"command": "uvx",
"args": [
"maskflow-mcp"
]
}
}
}Run this in your terminal
claude mcp add maskflow -- uvx maskflow-mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"maskflow": {
"command": "uvx",
"args": [
"maskflow-mcp"
]
}
}
}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.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"maskflow": {
"type": "stdio",
"command": "uvx",
"args": [
"maskflow-mcp"
]
}
}
}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.
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 maskflow, 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 32476 servers in this category
- Published to the registry more recently than 42% of the other 32476 servers in this category
- Basic checks equal to or better than 100% of the other 32476 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 MaskFlow PII proxy 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 (0.1.2) reached the registry 2 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, zanadir
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 desktop-commander
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Runs in the cloud★ 211Updated yesterday
Install
zanadir
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Runs on your computerUpdated today
Install
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.
maskflow-mcp
A Model Context Protocol proxy that wraps any MCP server and keeps PII out of your agent's tool traffic. It masks PII in outbound tools/call arguments before they reach the backend tool, and restores the originals in the results, with placeholders that stay consistent for the whole agent run.
Agents routinely pass user PII (names, emails, PAN, Aadhaar, phone numbers) straight into third-party MCP servers as tool arguments. This proxy is a drop-in shim that stops the real values at the boundary. It runs MaskFlow's detection engine, so the Indian identifiers (Aadhaar, PAN, GSTIN, UPI, IFSC, ABHA, Indian names / addresses) are covered alongside the generic PII.
MIT, no gates, no telemetry.
Install
pip install maskflow-mcpor, no install:
uvx maskflow-mcp stdio --backend "npx -y @modelcontextprotocol/server-github"
Pulls fastmcp (the 2.x line, which does not bundle LLM vendor SDKs). The first detection run downloads a small spaCy model; pass --patterns-only to skip it.
Use it
stdio (Claude Desktop, most agents)
Point the agent at maskflow-mcp and give it the real server as --backend:
// claude_desktop_config.json{ "mcpServers": { "github": { "command": "maskflow-mcp", "args": ["stdio", "--backend", "npx -y @modelcontextprotocol/server-github", "--pass-env", "GITHUB_TOKEN"] } } }
Or wrap a server already defined in a config file:
maskflow-mcp stdio --config ./claude_desktop_config.json --backend-name githubHTTP
maskflow-mcp http --backend https://example.com/mcp --host 127.0.0.1 --port 9000Options
| Flag | Default | Meaning |
|---|---|---|
--backend | – | Backend command line, or a URL |
--config / --backend-name | – | Read the backend from a Claude-Desktop-style JSON file |
--pass-env VAR | – | Forward an env var to a stdio backend (repeatable) |
--min-confidence | 0.5 | Detection threshold |
--patterns-only | off | Skip the spaCy NER pass (faster; drops bare-name / address detection) |
--mask-tool-results | off | Also mask PII the tool *introduced* in its result, not just unmask placeholders it echoed |
--session-ttl | 3600 | Lifetime of a per-connection session |
What is masked
tools/call arguments are walked (string and numeric *values* only, keys never) and masked through the connection's session. The result's text and structured content is unmasked, restoring placeholders the tool echoed. By default raw PII that the tool *adds* to a result passes through untouched; --mask-tool-results masks that too, so the agent never sees it.
tools/list, prompts/*, and resources/* pass through unchanged (resource content masking is not on by default).
PII safety
The token-to-value map lives in memory per connection and is never logged. Only masked values cross the wire to the backend. See docs/mcp.md in the MaskFlow repo for the design.