# Client Relay

> Use this tool when you need to synchronize AI conversation history and project context across multiple IDEs, such as Cursor and Antigravity, to ensure seamless collaboration and data consistency. It solves problems of data fragmentation and context switching by providing a unified interface to manage sessions, messages, and memory. Client Relay takes in user input and project data, and outputs synchronized conversation history and project context via a local SQLite database.

Canonical page: https://skillsregistry.net/skills/akshatmalik-bruh-client-relay  
JSON: https://api.skillsregistry.net/v1/skills/akshatmalik-bruh-client-relay

## Description

Client Relay synchronizes AI conversation history and project context across IDEs including Cursor and Antigravity using a local SQLite database. It provides six MCP tools for creating sessions, saving messages, adding memory, and retrieving context. Published as the chat-relay-mcp npm package and installable via npx.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/akshatmalik-bruh-client-relay)
- **Repository:** <https://github.com/akshatmalik-bruh/chatrelaymcp>

## 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": "akshatmalik-bruh-client-relay"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/akshatmalik-bruh-client-relay` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/akshatmalik-bruh-client-relay/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