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PopNx MCPMCP servers for people who use AI · explained in plain words

Flanner

by elandlabsversion 0.16.0i★ –iRuns on your computer
Registry nameio.github.jaysonmulwa/flanner

Install

Overview

Description from the maker (original English)

Keeps AI coding agents' plan and design markdown managed and versioned, for Claude Code and Codex.

PopNx MCP’s three pillars

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

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: Design, images & audio

Install

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

Before you install

  • Basic checks: 0 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": {
    "flanner": {
      "command": "uvx",
      "args": [
        "flanner"
      ]
    }
  }
}

Run this in your terminal

claude mcp add flanner -- uvx flanner

Open in Cursor

Or copy the settings yourself

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

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

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": {
    "flanner": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "flanner"
      ]
    }
  }
}

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 7, 2026

  • ! Caution

    Maker matches the repo

    The publisher (jaysonmulwa) is not the repo owner (elandlabs); someone else may have listed it

  • … 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 Design, images & audioi

  • More stars than 0% of the other 2193 servers in this category
  • Published to the registry more recently than 48% of the other 2193 servers in this category
  • Basic checks equal to or better than 33% of the other 2193 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 Flanner safe?

It passed 0 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 (0.16.0) reached the registry 30 days 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: Figma Context MCP, Claude Real Video, Figma MCP Server

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

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago
Install

Claude Real Video

by HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

Runs on your computer★ 2,284MITUpdated 2 months ago
Install

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago
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.

Flanner

A plan-file manager for AI coding agents, wired into Claude Code and other assistants over MCP (Model Context Protocol).

Why

AI agents write markdown constantly: design docs, migration plans, architecture notes. It piles up fast, scattered across your repo, quietly going stale, and easy to commit by accident. Flanner gives those files one home, versions them automatically as the agent revises, and keeps them out of git until you decide otherwise, with a browsable reading view and an audit trail on top.

No, I'm not convinced. But why?

Those plan files pile up in two directions at once: scattered across your projects locally, and scattered across open issues in your project-management tool. Flanner is the choke point for both, keeping you organized on disk and linked to the issue each plan belongs to.

Flanner is local-first, and stays that way when a team uses it. Plans sync directly between your machines over an encrypted connection — there is no server holding them, and no upload step. The hosted side (Flanner Mesh) issues identities and decides who may read what; it never sees plan contents and could not read them if it wanted to. Next after that: clean links out to the tools teams already work in, from product trackers and chat to second brains like Notion.

Features

  • MCP integration: exposes plan-file tools to Claude Code and Codex.
  • Automatic headers and versioning: every plan gets YAML frontmatter, and each revision is a new version with a full history.
  • Git protection: plans live in .plans/ and are kept out of commits automatically.
  • Agent integration: flanner init wires CLAUDE.md, AGENTS.md, and a guard hook so agents save plans through flanner instead of scattering raw markdown.
  • Memory: the durable context around a plan — a constraint, a rejected library, a fact about the environment — kept as Markdown files a later session can search. By default an agent proposes and you approve; it refuses anything that looks like a credential, and shares with a teammate only when somebody asks for it.
  • Skills: what your agents actually load. Skill packages arrive from a project, your home directory and every installed plugin at once, and when two share a name one wins silently. flanner skills scan reads them all and flanner skills doctor says which copy is in effect and what is wrong with the rest. A read: nothing in a package is executed.
  • Curb: what each agent can reach. flanner curb map checks every Claude Code and Codex launch for readable credentials and for the channels that could carry them away, and rates it High, Medium or Low with the rule behind it. Its output never names a credential or a location, whoever runs it; flanner curb show puts those in a window on your screen. flanner curb sweep finds secrets agents left behind in transcripts, sessions, instruction files, skills, MCP configs, shell history and .env files, and says which were sent to a model provider. A read: nothing is changed, and nothing leaves the machine unless you ask a secret's own issuer to check it. With Flanner Mesh, flanner curb policy takes one agent policy your organization signs, applies the changes that only tighten once you enrol, and holds anything else for your approval; flanner curb fleet shows admins each device's policy state and counts, from minimised reports each device signs. flanner curb ci, also a GitHub Action at actions/curb-ci, judges agent steps in CI workflows the same way and writes SARIF; flanner curb app finds an application's own LLM calls; and the agent-blast-radius skill lets an agent run the redacted commands itself. flanner curb attribution gives each agent a signing key of its own, kept in your OS credential store, so its commits are labelled; flanner curb verify says which agent key signed each commit, checked against your organization's signed key registry. A signature shows which key signed, not who wrote the code.
  • Messages (Team Mesh): teammates can message each other inside their agents, device to device. flanner messages send previews before it sends, and flanner tells an agent to show a teammate's message and never act on it.
  • Issue tracker links (off in this build): tie a plan to its Linear (or JIRA) issue; with a LINEAR_API_KEY, flanner verifies the issue and shows its live state, in the CLI and the dashboard. Built but not supported yet: set FLANNER_INTEGRATIONS=1 to turn them on.
  • Reading view: a browser dashboard to read, edit, and walk the history of plans (light and dark, fully offline).
  • Per-project config: customize the plan directory per repository.

Quick start

uv tool install flanner   # or: pipx install flanner, or: pip install flanner

cd your-project # a git repo where plans should live flanner init # sets up the database, MCP registration, and a project

Rather not install Python? The desktop app for Windows, macOS and Linux is the same flanner with nothing to install first: the web UI in a window, the command line, and the MCP server Claude and Codex use, with background sync and updates. Download it from flanner.io/download; desktop/README.md covers building and releasing it.

uv tool install gives flanner an environment of its own and puts both flanner and flanner-mcp on your PATH. Both matter: your agent spawns flanner-mcp by name, so a project virtualenv can hide it from an agent started outside that environment. pip install flanner works, with that caveat.

Then ask your agent to work with plans:

"Create an architecture plan for the auth service"

"Show me the history of the architecture plan"

And open the dashboard to browse them:

flanner web --open-browser     # http://localhost:8080

flanner init is safe to re-run. It detects your git root, creates .plans/, updates .gitignore, and installs the agent integration.

Three agents, three different files, and init handles all of it — there is no second command to remember. It writes a project-scoped .mcp.json that Claude Code reads, registers the server at user scope and in Claude Desktop's config, and adds managed blocks to CLAUDE.md and AGENTS.md. Codex reads AGENTS.md and registers MCP servers in ~/.codex/config.toml; when Codex is installed, init adds flanner's entry there, and prints the two lines to paste only when it cannot edit the file safely. flanner status shows a row per agent, each checked where that agent actually looks, and flanner setup re-runs the registration on its own if one of them needs repairing later.

--setup picks which of them you want, and repeats: flanner init --setup codex registers Codex and nothing else. --skip-claude registers with no agent, though the repository's own files are still written.

Adopting a repository somebody else set up? flanner init --sync also imports the plan files already committed in it, so flanner list shows them straight away.

CLI commands

flanner init [--project-root PATH] [--plan-dir DIR]     # set up a project

flanner status # projects, plan files, db path flanner list [--project NAME] [--output json] # list projects or a project's plans flanner sync [--project NAME] [--dry-run] # import existing .plans/ files flanner config NAME [--plan-dir DIR] [...] # change project settings flanner web [--port 8080] [--host 127.0.0.1] [--open-browser] flanner start [--port 8765] / flanner stop # MCP server in the background, over http flanner peer start / flanner peer stop # serve plans to teammates in the background flanner mem remember "..." --category fact # durable context for later sessions flanner mem recall "..." # search what earlier sessions knew flanner mem list / show ID / supersede ID --with "..." # browse, read, and correct flanner mem mode [off|explicit|suggest|auto_safe] # how much this project captures flanner mem share ID / flanner mem withdraw ID # give one to the team, or ask them to stop flanner skills scan / flanner skills doctor # what your agents load, and what is wrong flanner skills list [--all] / inspect NAME # browse them, or read every copy of one flanner skills observe enable / flanner skills report # record which get used; init asks flanner skills adopt NAME / install HASH / rollback ID # keep a copy, install it, put it back flanner skills share HASH / transfers / import ID # send one to the team; receiving is not installing flanner curb map [--agent A] [-- LAUNCH ...] # what each agent launch can reach flanner curb show # names and locations, in a window flanner curb inventory # agents, MCP servers, hooks, jobs flanner curb sweep [--validate] # secrets agents left behind (needs flanner[sweep]) flanner curb forget # delete Curb's reports and digest key flanner curb fix [--dry-run|--undo] # close what agents reach, after your OS says yes flanner curb test # prove each block with decoys (costs tokens) flanner curb decoys [--renew|--remove] # the decoys the tester planted flanner curb scrub FILE [--dry-run] # replace rotated secrets in a file (no undo) flanner curb log [--enable|--disable|--verify] # each tool call's metadata, hash-chained and signed flanner curb observed # what each agent has been seen using flanner curb policy [--check-in|--enrol|--approve] # your organization's signed agent policy flanner curb fleet # every device, checked by its own signature (admins) flanner curb ci [PATH] [--sarif F] [--fail-on L] # agent steps in CI workflows, as SARIF flanner curb app [PATH] [--sarif F] # LLM calls in an app's Python code flanner curb attribution [--setup|--rotate] # sign each agent's commits with its own key flanner curb verify [REV|RANGE] # which agent key signed each commit flanner register [--force] / flanner unregister # MCP registration with Claude Desktop flanner claude-info # integration status

Most MCP clients spawn their own copy of the server over stdio and need neither start nor stop. They are for a client that only speaks http, two editors sharing one server, or working with flanner on its own. The server binds 127.0.0.1 and no option widens that: every tool acts with the full authority of whoever started it, and nothing authenticates a caller.

Plan file format

Every managed plan carries YAML frontmatter, generated by the tools and never hand-written:

---

mcp_plan_file: true project_id: 3d816ecd-489a-4fa0-abe2-15ec93f60d5a plan_file_id: 59c34f9c-8471-47fc-97f2-8dcfefa15434 plan_name: architecture version: 2 created_by: claude


Architecture Plan

Your plan content here...

</d

Only the beginning is shown; read the rest in the repo

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