PLUR MCP — Persistent Memory for AI Agents

PLUR solves the amnesia problem: AI agents start every session with amnesia — you re-explain the project, repeat your preferences, and correct the same mistakes over and over. PLUR gives them a memory that persists.

It's open, local-first memory for AI agents. Your agent's corrections, preferences, and conventions are stored as plain-text engrams on your own machine — memory you can read, correct, and carry across sessions without vendor lock-in.

What It Does

• Persistent agent memory: Corrections, preferences, and conventions survive across sessions
• Local-first: All engrams stored as plain-text files on your machine — no cloud dependency
• Open source (MIT): Full transparency, no vendor lock-in
• Multi-agent aware: One memory store for all your MCP-compatible agents
• Human-readable: Engrams are plain text — you can read, edit, and prune them directly

Key Tools

Tool	Description
plur_store	Save a new memory engram
plur_search	Semantic search across stored engrams
plur_list	List all stored engrams
plur_delete	Remove an engram by ID

Quick Start

1. Install

git clone https://github.com/plur-ai/plur
cd plur
npm install
npm run build

2. Configure Your MCP Client

{
  "mcpServers": {
    "plur": {
      "command": "node",
      "args": ["/path/to/plur/dist/index.js"],
      "env": {
        "PLUR_STORE_PATH": "~/.plur/engrams"
      }
    }
  }
}

3. First Use

Once connected, your agent can call plur_store to remember anything: - "Remember I prefer TypeScript with strict mode" - "Store that our API base URL is https://api.corpusiq.io" - "Save the convention: always use async/await, never .then()"

On the next session, call plur_search and the agent retrieves what it needs.

Hermes Agent Integration

# ~/.hermes/config.yaml
mcp_servers:
  plur:
    command: "node"
    args: ["/home/hermes/tools/plur/dist/index.js"]
    env:
      PLUR_STORE_PATH: "~/.plur/engrams"

Use Cases for Business Operators

1. Self-improving agents: Your growth agent remembers what content performed well, what outreach templates worked, and which communities respond best
2. Cross-session consistency: Agents carry preferences, style guides, and business rules across restarts
3. Team memory: Share engram stores across team members for consistent AI behavior
4. Audit trail: Plain-text engrams let you inspect exactly what your agents have "learned"

How It Compares

Tool	Approach	Storage	License
PLUR	Local-first engrams	Your filesystem	MIT
Groundwork	Company-state feed	Cloud-hosted	Source-available
Memory (official)	Knowledge graph	Local file	MIT
Context7	Doc retrieval	Cloud	Proprietary

PLUR differentiates by being: (1) fully local, (2) plain-text readable, (3) MIT licensed, and (4) purpose-built for agent corrections and preferences rather than general knowledge retrieval.

Limitations

• No cloud sync (yet): Engrams are local — share via git, rsync, or your own sync solution
• New project: Early-stage, API may evolve
• Text-only: No structured data or multimodal memory (yet)
• Local setup required: Must install Node.js and clone the repo — no hosted version

Category

Memory & Knowledge — PLUR focuses specifically on agent corrections and preferences, making it complementary to general documentation tools like Context7 and company-state feeds like Groundwork.

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Discovered via mcp.so on July 24, 2026. Verified listing. GitHub: plur-ai/plur. 226 stars.