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Home/Servers/Elefante

Elefante

I
by io.github.amenophis1er

Open, Git-native memory protocol for MCP agents. Portable, versioned, human-editable.

Power your agent

Add this server

The publisher's own command. Not a PlugMCP endpoint.

Local command
npx -y [email protected]
Provider
Claude Code
claude mcp add io.github.amenophis1er-elefante -- npx -y [email protected]

Run in a terminal.

Claude Desktop
{
  "mcpServers": {
    "io.github.amenophis1er-elefante": {
      "command": "npx",
      "args": [
        "-y",
        "[email protected]"
      ]
    }
  }
}

claude_desktop_config.json

Step-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

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Questions

How do I install Elefante?
Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.
Does Elefante need an API key?
No required environment variable is listed on this record.
What transport does Elefante use?
Elefante runs locally over stdio.
When was Elefante last checked?
Last checked 2026-10-16. Open, Git-native memory protocol for MCP agents. Portable, versioned, human-editable.

Open, Git-native memory protocol for MCP agents. Portable, versioned, human-editable.

Elefante

The open, Git-native memory protocol for MCP agents: portable, inspectable, versioned, and human-editable.

Your agent's memory is a Git repo you own.
Every memory is a Markdown file you can read.
Every change is a commit you can audit.
Any MCP agent can connect to it.

Why

Every AI agent has its own memory system. Claude's works only with Claude. ChatGPT's works only with ChatGPT. They're all opaque, vendor-locked, and non-portable.

Elefante takes a different approach. Instead of optimizing for retrieval quality, it optimizes for ownership, auditability, and portability β€” the things that matter when memory is a first-class asset, not a hidden implementation detail.

QuestionAnswer
Who owns my agent's memory?You do. It's a Git repo.
What does my agent know about me?cat memories/user/*.md
What changed since last week?git log --since="1 week ago"
How do I use it across Claude, Codex, and Cursor?Point them at the same MCP server.
How do I back it up?Every clone is a full backup.
How do I undo a bad memory?git revert

Quick Start

# Install
npm install -g elefante-mcp

# Initialize vault (uses a private GitHub repo as storage)
elefante init [email protected]:yourname/my-memory.git

# Add your first memory
elefante add \
  --name "TypeScript strict mode" \
  --type user \
  --body "Always enable strict: true in tsconfig.json"

# Search
elefante search "typescript"

# Check status
elefante status

Connect to Your Agent

From the terminal (before starting Claude Code):

claude mcp add --scope user elefante -- npx -y elefante-mcp mcp

From inside Claude Code (during a session):

/mcp add --scope user elefante -- npx -y elefante-mcp mcp

Or manually β€” add to your MCP config (~/.claude.json, .cursor/mcp.json, etc.):

{
  "mcpServers": {
    "elefante": {
      "command": "npx",
      "args": ["-y", "elefante-mcp", "mcp"]
    }
  }
}

Cursor / VS Code / Codex β€” same config. Any agent that speaks MCP can read and write to the same vault.

Once connected, your agent gets 7 tools: memory_write, memory_read, memory_search, memory_list, memory_update, memory_delete, memory_sync.

Auto-Discovery

Elefante injects your top memories directly into the agent's system prompt at startup via MCP instructions. The agent sees your preferences, feedback, and project context without needing to search first.

No CLAUDE.md hacks. No "search my elefante memory" prompts. It just works.

Project-Aware Memory

Elefante auto-detects which project you're in and scopes memories accordingly. No configuration needed.

How It Works

When the MCP server starts, it reads the git remote from your working directory:

~/Projects/acme-api/   β†’  git remote = github.com:you/acme-api.git
                       β†’  profile = "you/acme-api"
                       β†’  memories scoped to this project

~/Projects/my-cli/     β†’  git remote = github.com:you/my-cli.git
                       β†’  profile = "you/my-cli"
                       β†’  different project, different memories

What Gets Scoped

You sayWhat happens
"Remember this project uses Postgres 16"Stored with profile: you/acme-api (project-scoped)
"Remember I prefer Bun over npm"Agent stores with profile: global β†’ null (applies everywhere)
"Remember the staging URL is staging.acme.io"Stored with profile: you/acme-api (project-scoped)

The agent decides based on context. User preferences and behavioral feedback are typically global. Project details and references are typically scoped.

What You See When You Search

Working in acme-api:
  βœ“ "Uses Postgres 16"              (profile: you/acme-api)
  βœ“ "Prefers Bun over npm"          (profile: null β€” global)
  βœ— "Uses SQLite"                   (profile: you/my-cli β€” different project)

Working in my-cli:
  βœ“ "Uses SQLite"                   (profile: you/my-cli)
  βœ“ "Prefers Bun over npm"          (profile: null β€” global)
  βœ— "Uses Postgres 16"             (profile: you/acme-api β€” different project)

Global memories always show up. Project memories only show up in their project.

Escape Hatches

Profile valueMeaning
(omitted)Auto-scope to detected project
"global"Explicitly global β€” no project scope
"all"Search/list across every project
"owner/other-repo"Explicitly target a different project

What a Memory Looks Like

Every memory is a Markdown file with YAML frontmatter. You can open it in any editor.

---
id: mem_a1b2c3d4e5f6
type: feedback
name: No database mocking in tests
description: Integration tests must use real database connections
profile: you/acme-api
importance: 3
tags: [testing, database]
created_at: "2026-04-14T10:30:00Z"
updated_at: "2026-04-14T14:22:00Z"
---

Do not mock the database in integration tests β€” use a real connection
to a test database.

**Why:** Mocked tests passed but the production migration failed because
the mock didn't reflect actual schema constraints.

**How to apply:** Use the test database helper (`createTestDb()`)
instead of jest mocks.

What a Git Log Looks Like

$ git log --oneline
f4a2c1e remember: No database mocking in tests
b3d8e7a remember: TypeScript strict mode preference
a1c9f2b update: REST to GraphQL migration deadline
9e7d4c3 forget: Outdated staging URL
2f8a6b1 Initialize elefante vault

Every write is remember:. Every update is update:. Every delete is forget:. Your memory has a clean, auditable history.

Vault Structure

~/.elefante/vault/
β”œβ”€β”€ .elefante/
β”‚   └── config.yaml              # Vault settings
β”œβ”€β”€ memories/
β”‚   β”œβ”€β”€ user/                    # Who the user is
β”‚   β”‚   └── mem_*.md
β”‚   β”œβ”€β”€ feedback/                # How the agent should behave
β”‚   β”‚   └── mem_*.md
β”‚   β”œβ”€β”€ project/                 # Active work context
β”‚   β”‚   └── mem_*.md
β”‚   └── reference/               # External resource pointers
β”‚       └── mem_*.md
β”œβ”€β”€ profiles/
β”‚   └── *.yaml                   # Named scopes for partitioning
└── index/
    β”œβ”€β”€ manifest.json            # All memory metadata (generated)
    └── search.json              # Search index (generated)

Memory Types

Four types. Intentionally constrained β€” a small taxonomy forces good classification.

TypeWhat to storeTypically scoped to
userFacts about you β€” role, preferences, expertiseGlobal
feedbackAgent behavior guidance β€” corrections, confirmationsGlobal
projectActive work context β€” goals, deadlines, decisionsProject
referenceExternal pointers β€” URLs, dashboards, toolsProject

Authentication

Elefante doesn't reinvent auth. It uses whatever Git credentials you already have.

Resolution order:

  1. Local git credentials (SSH keys, macOS Keychain, credential helpers)
  2. gh auth token (if GitHub CLI is installed)
  3. ELEFANTE_GITHUB_TOKEN environment variable
  4. ~/.elefante/config.json token field

If git or gh is authenticated, Elefante works with zero config.

CLI Reference

elefante init <repo-url>       Clone vault repo to ~/.elefante/vault/
elefante status                Vault status, sync state, memory count
elefante list [--type TYPE]    List memories with filters
elefante search <query>        Search by keyword
elefante read <id>             Read a specific memory
elefante add                   Create a memory
elefante delete <id>           Delete a memory
elefante sync                  Pull and push changes
elefante reindex               Rebuild search index
elefante mcp                   Start MCP stdio server

How It Compares

Elefante doesn't compete on retrieval quality. It competes on ownership.

ElefanteClaude/ChatGPT MemoryMem0 / Zep
You own the dataGit repo you controlVendor-controlledSelf-hosted or SaaS
Human-readableMarkdown filesNoNo
Version historyGit log for freeNoNo
Agent-agnosticAny MCP agentSingle vendorYes
Zero infrastructureGit + local processN/A (managed)Server + database
Offline accessLocal cloneNoNo
Auto project scopingDetects git remotePer-conversationManual
Semantic searchNot yet (planned)YesYes

"Why not Obsidian + MCP plugin?" β€” Obsidian is a tool for humans that agents can access. Elefante is a tool for agents that humans can access. Same data format (Markdown + Git), different design center.

Protocol

The full protocol specification β€” memory model, vault structure, MCP interface, concurrency model, indexing, security considerations β€” is in PROTOCOL.md.

License

MIT

How do I install Elefante?
Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.
Does Elefante need an API key?
No required environment variable is listed on this record.
What transport does Elefante use?
Elefante runs locally over stdio.
When was Elefante last checked?
Last checked 2026-10-16. Open, Git-native memory protocol for MCP agents. Portable, versioned, human-editable.

No tool list yet. Remote servers get one after the first health check.

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