# SerialMemoryServer

> SerialMemoryServer — sblanchard-serialmemoryserver. Use this tool when you need to manage temporal knowledge graphs and provide AI agents with a centralized memory system, solving problems of data consistency and retrieval in complex decision-making processes. It takes in AI agent requests and outputs relevant knowledge graph data, utilizing the Model Context Protocol (MCP) for seamless interaction. Ideal for applications requiring efficient knowledge management and retrieval, such as autonomous systems and cognitive architectures.

Canonical page: https://skillsregistry.net/skills/sblanchard-serialmemoryserver  
JSON: https://api.skillsregistry.net/v1/skills/sblanchard-serialmemoryserver

## Description

Model Context Protocol (MCP) server with temporal knowledge graph memory system for AI agents

## Trust

- **Trust score (0–1):** 0.79
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/sblanchard/SerialMemoryServer)

## 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": "sblanchard-serialmemoryserver"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sblanchard-serialmemoryserver` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sblanchard-serialmemoryserver/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