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  1. Home
  2. 🧠 Knowledge & Memory
  3. Elefante
Elefante logo
Health: ActiveRecent health check succeeded.Last checked 9/23/2026, 2:17:09 AM

Elefante

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository15 GitHub StarsTotal stargazers on GitHub for the source repository (15 stars).

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

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "elefante": {
      "command": "npx",
      "args": [
        "-y",
        "elefante-mcp"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Documentation Overview

Elefante

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

Code
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

bash
# Install
npm install -g elefante-mcp

# Initialize vault (uses a private GitHub repo as storage)
elefante init git@github.com: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):

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

From inside Claude Code (during a session):

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

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

config.json
{
  "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:

Code
~/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

Code
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.

markdown
---
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

Code
$ 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

Code
~/.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

Code
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

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
15
Stargazers on the source repository.
Last commit
5mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Elefante

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "elefante": { "command": "npx", "args": ["-y","elefante-mcp"] } }

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Technical Specs & Signals

Category🧠Knowledge & Memory
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedApr 20, 2026
2/6 checks healthy over the last 46d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars15
GitHub Star CountTotal stargazers on GitHub representing community popularity (15 stars).
Last commit5mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Apr 20, 2026
39Quality signal: Fair Β· 39/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6d ago via OSV.dev Β· elefante-mcp (npm)

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