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

projectmind

by Nodemint-devversion 0.6.0i★ 2iRuns on your computer
Registry nameio.github.Nodemint-dev/projectmind

How to install

What it does

Persistent project memory for AI coding agents: one compact digest instead of re-reading the repo.

  • Connects Runs on your computer
  • Account or key No key needed
  • Category Developer tools

Install

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

Passed 3/3 checks · Runs on your computer · ✓ Commands checked Nov 13, 2026

First: which AI do you use?

Pick your app and the steps appear below.

Works with Claude, with some setup first

Install Node.js on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone

  1. Install Node.js

    One time only; it works for every server that needs Node.js

    Open the Node.js download page ↗

  2. Open the Claude desktop app’s settings file

    SettingsDeveloperEdit Config

  3. Paste these settings and save the file

    {
      "mcpServers": {
        "projectmind": {
          "command": "npx",
          "args": [
            "-y",
            "@nodemint/projectmind",
            "mcp"
          ]
        }
      }
    }
  4. Quit Claude and open it again

  5. Try it

    Use projectmind and tell me what you can do for me, then show me one thing

    ✓ If Claude says it is using projectmind or shows a projectmind tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

ChatGPT cannot connect projectmind yet

projectmind runs on your computer, but ChatGPT can only connect servers that run on the web

What you can do instead

A · Use an app that can connect projectmind

  • Install Node.js on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
  • Install Node.js on your computer first (one time)
  • Install Node.js on your computer first (one time)
  • Install Node.js on your computer first (one time)

B · Others in Developer tools that work with ChatGPT

Picked from the most used in the same category, only ones that connect by address with no key

Works with Claude Code, with some setup first

Install Node.js on your computer first (one time)

  1. Install Node.js

    One time only; it works for every server that needs Node.js

    Open the Node.js download page ↗

  2. Open Terminal

    Mac: press Command+Space and type Terminal · Windows: open PowerShell

  3. Paste this command and press Enter

    claude mcp add --scope user projectmind -- npx -y @nodemint/projectmind mcp
  4. Type /mcp in Claude Code

    You should see projectmind listed as connected

  5. Try it

    Use projectmind and tell me what you can do for me, then show me one thing

    ✓ If Claude Code says it is using projectmind or shows a projectmind tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Cursor, with some setup first

Install Node.js on your computer first (one time)

  1. Install Node.js

    One time only; it works for every server that needs Node.js

    Open the Node.js download page ↗

  2. Click this button to open Cursor

    Open in Cursor

    Cursor asks you to confirm; click Install

  3. Open the AI chat in Cursor in Agent mode

  4. Try it

    Use projectmind and tell me what you can do for me, then show me one thing

    ✓ If Cursor says it is using projectmind or shows a projectmind tool in the answer, you are connected

Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with VS Code, with some setup first

Install Node.js on your computer first (one time)

  1. Install Node.js

    One time only; it works for every server that needs Node.js

    Open the Node.js download page ↗

  2. Click this button to open VS Code

    Open in VS Code

    VS Code asks you to confirm; click Install

  3. Open the AI chat in VS Code in Agent mode

  4. Try it

    Use projectmind and tell me what you can do for me, then show me one thing

    ✓ If VS Code says it is using projectmind or shows a projectmind tool in the answer, you are connected

Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

JSON settings are under “For developers” below

Stuck? Ask people who use projectmind💬 Discussion →
For developers: Terminal commands and JSON settings

Installed on your computer

Claude Code

claude mcp add --scope user projectmind -- npx -y @nodemint/projectmind mcp

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "projectmind": {
      "command": "npx",
      "args": [
        "-y",
        "@nodemint/projectmind",
        "mcp"
      ]
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "projectmind": {
      "command": "npx",
      "args": [
        "-y",
        "@nodemint/projectmind",
        "mcp"
      ]
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "projectmind": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@nodemint/projectmind",
        "mcp"
      ]
    }
  }
}

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

At a glance

Downloads per weeki
52/wk
Connection
Runs on your computer
Latest versioni
0.6.0
Published to registryi
Jul 6, 2026
Code last changedi
Jul 6, 2026
Maker
Nodemint-dev
Packages
npm: @nodemint/projectmind
Registry status
Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Run on your computer in

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

All apps, with pros and cons →

Related guides

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 14, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Nodemint-dev, which owns the repo

  • ✓ Pass

    Still maintained

    Code last changed 4 months ago

  • ✓ Pass

    Has a licence

    Uses MIT

  • – 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

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

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User reviews

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Compared with others in Developer toolsi

  • More stars than 77% of the other 5872 servers in this category
  • Published to the registry more recently than 19% of the other 5872 servers in this category
  • Basic checks equal to or better than 100% of the other 5872 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 projectmind safe?

It passed 3 of 3 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 4 months ago, and the latest version (0.6.0) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: REA, GitHub, Serena MCP: the IDE for your agent

Others in the same category

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

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

REA

Reverse engineer anything from your terminal or agent with one CLI and MCP server.

by morlutoWidely used↓ 388.7K/wk★ 457.7KUpdated 2 days ago

Runs on your computer

GitHub

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

by githubWidely used★ 34.4KUpdated 11 days ago

Computer or cloud

Serena MCP: the IDE for your agent

A powerful toolkit for coding, providing semantic retrieval and editing capabilities.

by oraiosWidely used↓ 35.2K/wk★ 31.4KUpdated 6 months ago

Runs on your computer

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.

projectmind

Persistent, compact project memory for AI coding agents. Your agent reads one small digest instead of re-scanning the codebase every session — and a local ledger shows you exactly how many tokens (and dollars) that saved.

Every AI coding session starts the same way: the agent has no memory of your project, so it re-reads files, re-derives your architecture, or asks you to re-explain decisions you made months ago. You pay for that in tokens, time, and wrong guesses — every single session, on every machine, for every teammate.

projectmind fixes this with a structured, persistent project map (.projectmind/map.json): your modules, their dependencies, your architectural decisions, your conventions, your domain glossary. The agent reads a ~400-token digest first, drills into single nodes only when needed, and writes back what it learns — so the *next* session (yours, a teammate's, or a different AI tool's) starts already knowing the project.

The digest scales with your project's *conceptual* size (modules, decisions), not its *byte* size — so the savings grow with the repo.

Quick start — one command

npm install -g @nodemint/projectmind

cd your-repo projectmind init

That single init does everything: scaffolds the map, seeds it from your repo layout, detects which AI agents are installed on your machine and wires each one (MCP server + a rules file carrying the live map), adds .projectmind/ to your .gitignore (the map stays local — nothing to push), and installs the git hook that keeps the map fresh on every commit.

Then the one step no tool can do for you: restart your agent (or start a new chat session). AI agents load their config and rules files at session start — a chat that was already open keeps its old context, and every session after that has the map automatically. Using the VS Code savings extension? Cmd+Shift+P → *"Developer: Reload Window"* once.

Want it available in every future project without even running `init`?

projectmind setup --global        # registers the MCP server once, user-wide

(projectmind init --bare scaffolds only, and projectmind setup re-wires agents on demand, if you prefer the pieces separately.)

See what it saves you — measured, not promised

The MCP server keeps a local savings ledger: every time your agent reads the map instead of scanning files, it records the tokens actually served vs. the estimated tokens of the files the agent would have read instead.

Check it anytime:

$ projectmind savings

projectmind savings (estimated — local ledger, never leaves this machine)

Total saved: ~20.5k tokens across 22 map read(s) ≈ $0.0614 at sonnet-tier input pricing ($3/MTok, as of 2026-06) Today: ~20.5k tokens (22 read(s))

By tool: mind_digest 12 reads ~18.5k saved mind_query 6 reads ~1210 saved mind_context 4 reads ~712 saved

Methodology: tokens ≈ ceil(bytes/4); baseline = files the agent would have read instead.

The dollar figure needs zero configuration: it defaults to Sonnet-tier input pricing from a built-in table of published rates (Haiku $1 / Sonnet $3 / Opus $5 / Fable $10 per MTok input, as of June 2026), and says exactly which assumption it used. If you run a different model, set savings.model (or an exact savings.inputPricePerMTok) in .projectmind/config.json — but nobody has to.

*(Real output from a scripted day of agent work on the sample project in test/fixtures/ — 12 session starts, 6 module drill-ins, 4 task-context reads. Reproduce the per-session number with npm run benchmark.)*

VS Code status bar: the integrations/vscode extension shows a live ✦ ~20.5k tokens saved counter that reads the same local ledger. Zero dependencies, zero network.

The ledger is honest by design: every number is labelled an estimate (ceil(bytes ÷ 4), the rough English+code average), savings are floored at zero, and the file is gitignored — it's your private data, on your machine, deletable at any time.

One deliberate gap, stated plainly: the ledger only counts *tool calls* (mind_digest, mind_query, mind_context). The embedded digest described below never requires a tool call — that's the whole point — so its savings don't show up as a number here. projectmind savings names which rules files carry it instead of inventing a token count we can't actually observe.

Session handoff — pick up exactly where you left off

The thing every agent session loses is *working state*: what you were in the middle of, what's next, the gotcha you just discovered. Code graphs can't capture it; chat history dies with the session. projectmind carries it over:

$ projectmind digest

shopflow-api — project map

Order-management HTTP API with JWT auth, backed by PostgreSQL. Stack: node, express, postgres

⏪ Handoff from last session (2026-07-02)

Adding refund support to orders-route; next: write the refund tests

Your agent calls mind_handoff before the session ends (or before its context gets compacted); the note leads the very next digest, so the next session — tonight on your laptop, tomorrow on your desktop, or a different AI tool entirely — resumes in one read instead of re-deriving the task. Notes live in your gitignored local overlay: personal working state, never committed, cleared with mind_handoff({clear: true}) when done. Humans can use it too: projectmind handoff "note".

Works everywhere your team works

No language assumptions, no platform assumptions: the full test suite (85 tests, including the git-hook end-to-end and offline-guarantee tests) runs in CI on Linux, macOS, and Windows × Node 18/20/22. Paths, globs, atomic renames, and the installed git hook are exercised on all three. The map format is plain JSON — nothing OS-specific is ever written to your repo.

Verified against real open-source repos (fresh clone → projectmind init --seed, 2026-07-02):

RepoStack detectedSeeded nodesRepo size (est.)Digest
expressjs/expressnodeexamples, lib, test~175k tokens / 152 files~86 tokens
pallets/flaskpythonexamples, src, tests~153k tokens / 104 files~111 tokens
flutter/pinballdart, flutterlib, packages, test, web~513k tokens / 637 files~99 tokens

That's the core scaling property in the wild: the digest tracks a project's *conceptual* size, staying ~100 tokens whether the repo is 150k or 500k tokens. (A freshly seeded digest is a starter skeleton — a curated map with decisions and conventions lands around 400 tokens, like the benchmark fixture. We quote the honest per-session savings number — 78.9% — from the benchmark, not from these whole-repo ratios.)

How it works

flowchart LR

subgraph agents["Your AI agents"] A1[Claude Code] A2[Cursor] A3[Gemini / Codex / Copilot] end subgraph pm["projectmind"] MCP["MCP server\n(stdio, 6 tools)"] CORE["core\n(atomic writes, schema-validated)"] HOOK["git post-commit hook\n+ watch mode"] end subgraph repo["Your repo"] MAP[".projectmind/map.json\nnodes · edges · decisions\nconventions · glossary"] DIG[".projectmind/digest.md\n+ embedded in CLAUDE.md etc."] end LEDGER[".projectmind/ledger.json\nlocal savings ledger (gitignored)"]

A1 <--> MCP A2 <--> MCP A3 <--> MCP MCP --> CORE HOOK --> CORE CORE <--> MAP CORE --> DIG MCP --> LEDGER

Two update paths keep the map current without burning tokens:

  • Deterministic: the git hook (and optional projectmind watch) map changed files to modules via globs and bump freshness. Pure local computation, zero LLM.
  • Agent-recorded: when the agent makes an architectural decision or learns a convention, it calls mind_update — a few tokens once, instead of re-discovery every session.

There is deliberately no background LLM summarization — that would burn the tokens this tool exists to save.

What the agent actually reads

# shopflow-api — project map

Order-management HTTP API with JWT auth, backed by PostgreSQL. Stack: node, express, postgres

Active

  • auth: Issues/verifies JWT access tokens; exposes requireAuth Express middleware. [active]
  • orders-route: Create and list orders for the authenticated user; totals in integer cents. [active]

Modules

  • db: PostgreSQL pool wrapper: query() helper and withTransaction().

…

Key decisions

  • Store money as integer cents, never floats. (2026-06-10)
  • JWT for stateless auth instead of server sessions. (2026-06-15)

Conventions

  • Never read process.env outside src/config.js.

…

~412 tokens for the whole thing. The long fields (notes, rationale, file lists) are excluded from the digest and only surface through mind_query — cheap by default, detail on demand.

MCP tools

ToolPurpose
mind_digest()Read first every session. The compact map.
mind_context({files})Task-scoped. Only the modules a task touches + their direct deps. The cheapest read when you know the files.
mind_query(node)Full detail on one node: files, notes, edges.
mind_search(term)Find nodes / decisions / glossary by keyword.
mind_update(delta)Record a structural change, decision, or convention.
mind_handoff(note)Leave a "resume here" note that leads the next session's digest.
mind_stats()Map size, digest cost, and your savings ledger.

One-command agent wiring — and it doesn't depend on the model choosing to read it

projectmind setup idempotently writes the MCP config and a workflow rules block for each agent — merging into existing configs, never clobbering (an unparseable config is backed up and skipped).

Here's the part that matters: MCP tools are a *nudge* — no server can force a model to call one, so an agent can (and sometimes will) skip mind_digest on a plain "explain this project" question, especially mid-task. But rules files (CLAUDE.md, .cursorrules, .windsurfrules, GEMINI.md, AGENTS.md, .github/copilot-instructions.md) are loaded into every agent's context unconditionally, with zero model choice involved — that's the actual mechanism, not a coincidence. So setup doesn't just write instructions to call mind_digest; it embeds the live digest itself between markers, and every subsequent mind_update, CLI edit, git-commit hook run, or watch save re-syncs it automatically. The project map is present in context from message one, on every agent, with no tool call required at all

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