# Memory Bank

> Use this tool when you need to enhance AI agents with vector-native memory capabilities, solving problems of knowledge retention and retrieval in applications such as conversational interfaces, recommender systems, and collaborative filtering. It provides a flexible interface for multiple database backends and supports various input formats, outputting contextualized information and performance metrics. Ideal for use cases requiring dynamic embedding configuration, fine-grained access control, and scalable memory management.

Canonical page: https://skillsregistry.net/skills/protocol-lattice-memory-bank  
JSON: https://api.skillsregistry.net/v1/skills/protocol-lattice-memory-bank

## Description

Production-ready MCP server providing vector-native memory capabilities for AI agents with support for multiple database backends including PostgreSQL with pgvector, Qdrant, MongoDB Atlas Vector Search, and in-memory storage. Features two-tier memory architecture with short-term session buffers and long-term vector storage, shared memory spaces with fine-grained ACL controls and TTL support, and dynamic embedding configuration through AutoEmbedder supporting OpenAI, Gemini, and local models. Exposes comprehensive tools for memory management, contextual retrieval, collaborative spaces, and performance monitoring.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/protocol-lattice-memory-bank)
- **Repository:** <https://github.com/protocol-lattice/memory-bank-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": "protocol-lattice-memory-bank"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/protocol-lattice-memory-bank` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/protocol-lattice-memory-bank/pull`

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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