# MCP Server with Durable History

> MCP Server with Durable History — gavinarori-mcp-system-design-and-architecture-in-typescript. Use this tool when you need to manage concurrent client conversations and retain conversation history across sessions. It solves problems of lost conversation context and improves user experience by providing a durable and consistent chat history. The tool takes in client inputs and outputs a persistent conversation record, ideal for use cases requiring multi-session dialogue management.

Canonical page: https://skillsregistry.net/skills/gavinarori-mcp-system-design-and-architecture-in-typescript  
JSON: https://api.skillsregistry.net/v1/skills/gavinarori-mcp-system-design-and-architecture-in-typescript

## Description

An MCP server that provides a chat tool with stateless instances and external session state, enabling durable conversation history and concurrent client handling.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/k6e1t57m4n)
- **Repository:** <https://github.com/gavinarori/MCP-system-design-and-architecture-in-typescript->

## 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": "gavinarori-mcp-system-design-and-architecture-in-typescript"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gavinarori-mcp-system-design-and-architecture-in-typescript` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gavinarori-mcp-system-design-and-architecture-in-typescript/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