tulayngmamamo

MCP server enabling bidirectional communication between Claude Code CLI and OpenAI Codex CLI. Allows AI assistants to delegate tasks (research, code review) to each other and receive responses.

Features

- AI-to-AI Communication: Claude and Codex can send messages to each other
- Queue-First Delivery: Fire-and-forget messaging for both Claude and Codex
- Agent Personas: Architect (critical code review) and Oracle (debugging/root cause analysis) personas
- Conversation Tracking: SQLite-backed message history
- memorantado Integration: Sync conversation summaries to knowledge graph
- Unlimited Connections: Multiple Claude Code clients can connect simultaneously

Installation

$3

``bash


Global install

npm install -g tulayngmamamo
tulayngmamamo

Or run directly with npx

npx tulayngmamamo
`

$3

`bash
git clone https://github.com/alfredosdpiii/tulayngmamamo.git
cd tulayngmamamo
npm install
npm run build
npm start
`

Server runs at http://127.0.0.1:3790

MCP Configuration

Add to your .mcp.json or MCP client configuration:

$3

Start the server first (tulayngmamamo or npx tulayngmamamo), then configure your MCP client:

`json
{
"mcpServers": {
"tulayngmamamo": {
"type": "http",
"url": "http://localhost:3790/mcp"
}
}
}
`

$3

`json
{
"mcpServers": {
"tulayngmamamo": {
"command": "npx",
"args": ["tulayngmamamo", "--stdio", "--client-id", "claude"]
}
}
}
`

For Codex, use "codex" as the client id instead of "claude".

MCP Tools

| Tool | Description |
|------|-------------|
| who_am_i | Returns client identity (claude/codex) |
| send_message | Send message to another AI (supports agent parameter) |
| delegate_research | Request research on a topic |
| request_review | Request code/architecture review |
| create_conversation | Start a new conversation |
| get_history | Retrieve conversation messages |
| share_context | Share files/snippets between AIs |
| list_conversations | List active/completed conversations |
| close_conversation | Close and optionally summarize a conversation |

Agent Personas

When sending messages to Codex, you can specify an agent persona:

| Agent | Use When | Behavior |
|-------|----------|----------|
| architect | Architecture questions, code review | Critical analysis, challenges assumptions, examines codebase |
| oracle | Debugging, "why" questions | Root cause analysis, strategic reasoning, action steps |

Auto-selected based on message content, or specify explicitly:

`
send_message(target="codex", content="Review this code", agent="architect")
send_message(target="codex", content="Why is this failing?", agent="oracle")
`

$3

The Architect acts as a critical technical partner who:
- Examines the codebase independently before responding
- Agrees when you're right (but explains why)
- Disagrees when they see problems (with specific alternatives)
- Never just rubber-stamps suggestions

$3

The Oracle acts as a strategic advisor who:
- Focuses on root cause analysis
- Provides concrete action steps
- Helps understand "why" questions
- Uses strategic reasoning for complex problems

Configuration

| Environment Variable | Default | Description |
|---------------------|---------|-------------|
| TULAYNGMAMAMO_PORT | 3790 | Server port |
| TULAYNGMAMAMO_DB | ~/.tulayngmamamo/tulayngmamamo.sqlite | Database path |
| MEMORANTADO_URL | http://127.0.0.1:3789 | memorantado integration URL |
| TULAYNGMAMAMO_CLIENT_ID | auto-detect (fallback: claude) | Client identity for stdio mode (claude or codex) |
| TULAYNGMAMAMO_CODEX_MODEL | gpt-5.3-codex | Default Codex model |
| TULAYNGMAMAMO_CODEX_REASONING_EFFORT | xhigh | Default Codex reasoning effort |

Architecture

`
Claude Code CLI <----> tulayngmamamo <----> Codex CLI
| | |
| | |
MCP Client MCP Server MCP Server
(this project) (codex mcp-server)
`

$3

1. Client sends message via MCP tool
2. Message is persisted and enqueued in SQLite (message_queue)
3. Queue processor delivers when target client is online
4. Target replies with a new message linked by response_to_id
5. Sender fetches replies via get_response` or conversation history

License

MIT