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

Plur

by plur-aiversion 0.23.0i★ –iRuns on your computer
Registry nameio.github.plur-ai/plur

Install

Overview

Description from the maker (original English)

Open, local-first engram memory for AI agents: read, correct, delete; shared over MCP.

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: Search & AI memory

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

  • npmNode.js installed (for the npx 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": {
    "plur": {
      "command": "npx",
      "args": [
        "-y",
        "@plur-ai/mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add plur -- npx -y @plur-ai/mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "plur": {
      "command": "npx",
      "args": [
        "-y",
        "@plur-ai/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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "plur": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@plur-ai/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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account plur-ai, 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 Search & AI memoryi

  • More stars than 0% of the other 7275 servers in this category
  • Published to the registry more recently than 83% of the other 7275 servers in this category
  • Basic checks equal to or better than 100% of the other 7275 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 Plur 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 (0.23.0) reached the registry 8 days 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: Context7, Codebase Memory, Exa

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

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month
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.

PLUR — Your agents share the same memory

Persistent, open memory for AI agents — local-first, zero-cost, shared across MCP tools (Claude Code, Codex, Cursor, OpenCode, Hermes, OpenClaw). Your agent's memory is plain-text engrams you can read, correct, and delete — not weights you can't.

plur.ai · Benchmark · Engram Spec · npm · Comparisons

Benchmarks

PLUR is memory, not just retrieval — so we measure it on more than one axis, on the full corpus, and we publish the harness so you can reproduce every number.

Retrieval recall — full LongMemEval-S (N=500), R@5, fully local:

StackR@5Notes
BM25 only92.2%no embedder — fully airgapped
Hybrid (BGE-small, shipping default)95.6%local embedder; one-time model download
+ BGE-reranker-v2-m397.6%local cross-encoder, max quality — opt-in, ≈5s p50 on CPU

Numbers come from plur-ai/plur-bench, which is the source of truth for every benchmark figure PLUR publishes. Where an in-repo number and a plur-bench number disagree, plur-bench wins — it is the reproducible harness, and it is what CI regression-checks.

Chunk granularity, canonical-doc scoring, corpus SHA256 pinned — reproduce it in plur-ai/plur-bench. No cloud call is required for any of these numbers (an *optional* cloud embedder, openai-3-large, reaches 97.0% hybrid). A faster reranker — ms-marco-minilm-l6 (p50≈245ms vs BGE's ≈5s on CPU) — trades a little recall for sub-second latency.

Run it yourself — and tell us what you get. The harness is plur-ai/plur-bench: CPU-runnable, no API key needed for the local path, corpus auto-fetched and SHA-verified. If you run it, we'd genuinely love to see your numbers — open an issue or discussion with your results, especially if they don't match ours. Independent reproduction is worth more than any number we publish, and we'll gladly credit you.

Retrieval ≠ answer accuracy — and we report them separately, never conflated. End-to-end (LLM-judge) answer accuracy with the reranker stack is 60.5%, versus 52.0% for dumping full context into the prompt and 5.5% with no memory at all.

Agent-task impact — same task, with memory vs without: Haiku + PLUR outperforms Opus *without* it at roughly 10× less cost; house rules 12–0 across Haiku, Sonnet, and Opus.

Operational — local-first, zero-cost search, data-sovereign by design.

*More in progress: LoCoMo, agentic task suites, cross-tool portability, decay / contradiction correctness.* Full methodology →

The idea

You correct your agent's coding style on Monday. On Tuesday, it makes the same mistake. You explain your architecture in Cursor. That night, Claude Code has no idea.

PLUR fixes this. Install it once, and corrections, preferences, and conventions persist — across sessions, tools, and machines. Your memory is stored as plain YAML on your disk. No cloud, no API calls, no black box.

The interesting part: in our tool-routing and local-knowledge benchmark, Haiku with PLUR memory outperformed Opus without it — 2.6x better on tool routing, at roughly 10x less cost. Turns out the bottleneck isn't model intelligence. It's context.

The model is rented; your memory is owned. Swap Haiku for Opus for whatever ships next month — the reasoning is a commodity you don't control. The part that's *yours* — everything the agent has learned about your work, your corrections, your conventions — shouldn't live in someone else's cloud or be baked into weights you can't read. PLUR keeps it in plain files on your disk, in an open format you can inspect, correct, and delete. That's what owning your intelligence actually means.

Install

Requires Node.js 20 or newer. Install both packages so editor configurations can use the installed MCP server:

npm install -g @plur-ai/cli@latest @plur-ai/mcp@latest

plur init plur doctor

Restart your editor after setup. plur doctor checks the configuration and MCP handshake, and downloads the search model if it is missing and downloads are allowed. Search runs locally after that download; without the model it falls back to keyword search.

Tell your agent
Set up PLUR memory for me: install @plur-ai/cli@latest and @plur-ai/mcp@latest globally, run `plur init`, then `plur doctor`. Show me any checks that fail.
Claude Code

plur init creates the local store at ~/.plur/, registers the user-scoped MCP server in ~/.claude.json, and writes global hooks to ~/.claude/settings.json. A project .mcp.json is a separate project-scoped configuration; ~/.claude/mcp.json is not the user-scoped registration path. The hooks inject memory and close session state when Claude Code emits SessionEnd. Run init again after upgrading PLUR to refresh its configuration.

For multi-project setups, use domain/scope to separate knowledge:

cd ~/projects/my-app

plur init --domain myapp --scope project:my-app

This creates a .plur.yaml in the project with defaults that hooks apply automatically. Engrams learned in that project are tagged; recall filters by scope but always includes global knowledge.

Set scope per engram, by content. Scope is not a once-per-session setting — every plur_learn call takes its own scope, chosen from what the engram is about. Team/shared knowledge goes to a team scope (e.g. group: / , used by PLUR Enterprise); project details to project: ; personal preferences stay local. Don't let team-relevant knowledge fall back to global by omitting scope — global leaks into every project and (with a team store configured) never reaches the team. plur_session_start lists the remote scopes a token can write to.

Upgrade
npm install -g @plur-ai/cli@latest @plur-ai/mcp@latest

plur init plur doctor

Restart the editor so it launches the updated MCP server.

Cursor

From your project root:

plur init --cursor

This writes .cursor/mcp.json, .cursor/hooks.json and .cursor/rules/plur-memory.mdc. Cursor uses the reduced cursor tool profile: core tools are direct, and other operations are available through plur_admin. Call plur_admin with { "action": "help" } to discover their current names and arguments.

Codex
plur init --codex

Registers a new MCP server via codex mcp add in ~/.codex/config.toml, writes lifecycle hooks to ~/.codex/hooks.json (CODEX_HOME overrides the directory), and adds a PLUR section to AGENTS.md. Auto-detected when ~/.codex/ exists.

To upgrade an existing Codex installation:

npm install -g @plur-ai/cli@latest @plur-ai/mcp@latest

plur init --codex plur doctor --codex

Init updates recognized older PLUR launch pins in place, preserving environment settings, timeouts, tool policies and comments. It preserves newer pins and custom or HTTP servers. Use --keep-codex-mcp to retain an intentional older launch entry. Restart Codex after changing its configuration.

For remote stores using plur remote --token-env NAME, both remote and init --codex add the required variable names to Codex's env_vars; they never copy token values into its config. The variable must also be available to the process that launches Codex. A variable exported in PowerShell does not prove that a separately launched desktop app inherited it.

plur doctor --codex starts the MCP command from the Codex user config with Codex-style environment filtering, checks its reported version against the CLI, and reports missing token forwarding or values. It does not check project/profile overrides, another running application's environment, hook trust, or a remote write. --no-handshake reports the runtime as unverified and exits nonzero. Verify saving and recalling a test memory in the actual Codex session before treating desktop setup as complete. Native Windows and WSL2 have separate home directories and registrations; run setup in each environment you use.

Injection uses hybrid search (BM25 + embeddings) with an automatic BM25 fallback if the embedder is slow or unavailable. Set PLUR_HOOK_HYBRID=0 to force BM25 (applies to the Antigravity hooks too; PLUR_CODEX_HYBRID is honoured as an alias). PLUR_HOOK_HYBRID_DEADLINE_MS tunes the fallback deadline — keep it below your harness's hook timeout (Codex 25s, Antigravity 20s).

One manual step after install: open Codex, run /hooks, and trust the PLUR entries. Codex fingerprints every hook and refuses to run untrusted ones — *silently*, with no warning and a zero exit code. Until you trust them, memory simply never loads. plur doctor says so too.

OpenCode
plur init --opencode

plur doctor

This adds the memory plugin and MCP tools to ~/.config/opencode/opencode.json, or to the existing opencode.jsonc when no .json exists. OPENCODE_CONFIG_DIR takes precedence; otherwise XDG_CONFIG_HOME/opencode overrides the default directory.

The MCP command uses Node and the installed @plur-ai/mcp entry when available. Init updates an older exact @plur-ai/opencode pin to the plugin version shipped with the CLI while preserving comments, formatting and unrelated settings. Newer pins, tags and unpinned entries remain unchanged. Use --keep-opencode-plugin to retain an intentional old pin. Restart OpenCode to load the changed configuration. Plugin details.

Which integration you get

Every MCP client can call PLUR's tools. Only some have an *adapter* — the hooks and always-on context that make memory load automatically instead of waiting for the agent to think of it. Without one, recall and learning depend entirely on the model choosing to call the tools, which degrades badly under context pressure.

HarnessToolsAuto-injection + enforcement
Claude Code✅✅ hooks + CLAUDE.md
Codex✅✅ hooks + AGENTS.md (trust /hooks once)
Cursor✅✅ hooks + rules
OpenCode✅✅ memory plugin + MCP tools
OpenClaw✅✅ ContextEngine plugin
Hermes✅✅ plugin
Antigravity CLI (agy)✅✅ hooks + AGENTS.md
Windsurf, Gemini CLI, other MCP clients✅❌ tools only

If your harness is in the last row, paste the PLUR section from CLAUDE.md into its own context file (AGENTS.md, GEMINI.md, …) as an interim measure — that restores the instruction layer, though not automatic injection.

Antigravity CLI (agy)
plur init --antigravity

Writes hooks and the MCP server into agy's global config (~/.gemini/config/) and adds a PLUR section to AGENTS.md. Auto-detected when ~/.gemini/antigravity-cli/ exists. No trust step — agy runs

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

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