# Mem0

> Use this tool when you need to retain context and knowledge across sessions while maintaining data privacy, and want a self-hosted memory system that integrates with multiple LLM providers and offers advanced graph intelligence and vector search capabilities. It solves problems of information loss and context switching, providing persistent and intelligent memory for projects and preferences. Ideal for developers seeking secure and private knowledge management, Mem0 accepts large text inputs and outputs graph-based relationships and decision rationale.

Canonical page: https://skillsregistry.net/skills/subhashdasyam-mem0-server  
JSON: https://api.skillsregistry.net/v1/skills/subhashdasyam-mem0-server

## Description

A self-hosted memory system that provides persistent, intelligent memory capabilities through dual-server architecture combining Mem0 AI with MCP protocol integration. Built by Subhash Dasyam, it features automatic project isolation, smart text chunking for large inputs, and advanced graph intelligence through Neo4j for tracking memory relationships, decision rationale, and knowledge evolution over time. The implementation supports multiple LLM providers (Ollama, OpenAI, Anthropic) with configurable embedding models, includes token-based authentication, and offers both vector search through PostgreSQL/pgvector and graph analysis capabilities, making it ideal for developers who want context retention, preferences, and project-specific knowledge across sessions while maintaining complete data privacy through local deployment.

## Trust

- **Trust score (0–1):** 0.78
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/subhashdasyam-mem0-server)
- **Repository:** <https://github.com/subhashdasyam/mem0-server-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "subhashdasyam-mem0-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/subhashdasyam-mem0-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/subhashdasyam-mem0-server/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt