MemoryGraph

v1.0.0Knowledge & Memorystable

A graph-based MCP server that provides AI coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. It leverages graph structures to handle temporal queries and relational paths that

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What is MemoryGraph?

MemoryGraph is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to graph-based mcp server that provides ai coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. it leverages graph structures to ha...

A graph-based MCP server that provides AI coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. It leverages graph structures to handle temporal queries and relational paths that

This server falls under the Knowledge & Memory and Coding Agents categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • A graph-based MCP server that provides AI coding agents with

Use Cases

Store and recall coding patterns and architectural decisions across projects.
Track complex relationships and dependencies in codebases with graph-based memory.
Retrieve contextual knowledge from previous coding sessions.
memory-graph

Maintainer

LicenseMIT License
Languagepython
Versionv1.0.0
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx memorygraph

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use MemoryGraph

MemoryGraph is a graph-based MCP server that gives AI coding agents persistent, structured memory across sessions using explicit node-and-edge relationships. Unlike flat key-value stores, it supports seven relationship categories, bi-temporal tracking, and fuzzy contextual search, making it possible to recall not just what was stored but how pieces of knowledge relate to each other. Developers use it to preserve architectural decisions, coding patterns, and project context so AI assistants can pick up exactly where they left off.

Prerequisites

  • Python 3.10 or higher (pipx recommended for isolation)
  • An MCP-compatible client such as Claude Desktop or Claude Code CLI
  • Optional: Neo4j or FalkorDB for graph-native backends
  • Optional: MEMORYGRAPH_API_KEY for the hosted cloud backend
1

Install memorygraphMCP

Install using pipx for the recommended isolated environment. The default backend uses SQLite and requires no additional database setup.

pipx install memorygraphMCP
# For Neo4j backend support:
# pipx install "memorygraphMCP[neo4j]"
# For FalkorDB backend:
# pipx install "memorygraphMCP[falkordb]"
2

Add to Claude Desktop or Claude Code

Register the server with your MCP client. The default profile uses the local SQLite backend and needs no environment variables.

# Claude Code CLI (recommended):
claude mcp add --scope user memorygraph -- memorygraph

# With extended tools profile (adds statistics and advanced relationship queries):
claude mcp add --scope user memorygraph -- memorygraph --profile extended
3

Optional: configure the cloud backend

To sync memory across machines, obtain an API key from memorygraph.dev and pass it via environment variable.

claude mcp add --scope user memorygraph \
  --env MEMORYGRAPH_API_KEY=mg_your_key_here \
  -- memorygraph --backend cloud
4

Optional: configure Neo4j backend

If you prefer a native graph database backend, point MemoryGraph at a running Neo4j instance using the three Neo4j environment variables.

export MEMORY_NEO4J_URI="bolt://localhost:7687"
export MEMORY_NEO4J_USER="neo4j"
export MEMORY_NEO4J_PASSWORD="your_password"
memorgraph --backend neo4j
5

Verify the server is running

After adding the server, restart your MCP client. Ask the AI to store a test memory to confirm the connection is live.

MemoryGraph Examples

Client configuration

Claude Desktop configuration for MemoryGraph using the default SQLite backend with extended tools.

{
  "mcpServers": {
    "memorygraph": {
      "command": "memorygraph",
      "args": ["--profile", "extended"]
    }
  }
}

Prompts to try

Example prompts that demonstrate storing, recalling, and relating knowledge with MemoryGraph.

- "Remember that we use bcrypt for password hashing in this project and tag it as security, authentication"
- "What coding patterns have you stored about authentication?"
- "Create a relationship between the bcrypt pattern and the user registration module — it solves the password storage problem"
- "Give me a session briefing — what do you know about this codebase?"
- "Show me all memories tagged with 'architecture' created this week"

Troubleshooting MemoryGraph

memorygraph command not found after installation

Ensure pipx's bin directory is in your PATH. Run 'pipx ensurepath' and restart your terminal. Alternatively, install with 'pip install --user memorygraphMCP' and check ~/.local/bin is in PATH.

Neo4j connection refused or authentication failed

Verify Neo4j is running ('neo4j status') and that MEMORY_NEO4J_URI, MEMORY_NEO4J_USER, and MEMORY_NEO4J_PASSWORD are all set correctly. The default bolt port is 7687.

Memories from previous sessions are not appearing

Confirm you are using the same backend and data directory across sessions. For the default SQLite backend, the database file lives in the memorygraphMCP data directory — do not delete it between sessions. For cloud backend, verify your MEMORYGRAPH_API_KEY is consistent.

Frequently Asked Questions about MemoryGraph

What is MemoryGraph?

MemoryGraph is a Model Context Protocol (MCP) server that graph-based mcp server that provides ai coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. it leverages graph structures to handle temporal queries and relational paths that It connects AI assistants to external tools and data sources through a standardized interface.

How do I install MemoryGraph?

Follow the installation instructions on the MemoryGraph GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with MemoryGraph?

MemoryGraph works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is MemoryGraph free to use?

Yes, MemoryGraph is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.

Browse More Knowledge & Memory MCP Servers

Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

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

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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