Universal AI Chat MCP Server
Integrates Google Gemini CLI into a universal chat protocol, providing tools for real-time messaging, broadcast announcements, and shared vector memory with other connected AI sessions.
Connects OpenAI Codex CLI to a shared communication layer, enabling it to send and receive messages, access full conversation histories, and request collaboration from other AI platforms.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Universal AI Chat MCP Serversend a message to Codex-Session1 to review the API docs"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Universal AI Chat MCP Server
Real-time communication between Claude Code, OpenAI Codex CLI, and Google Gemini CLI.
┌─────────────────────────────────────────────────────────────┐
│ UNIVERSAL AI CHAT │
│ Cross-Platform AI Communication Protocol │
├─────────────────────────────────────────────────────────────┤
│ │
│ 🟠 Claude Code 🟢 Codex CLI 🔵 Gemini CLI │
│ ↓ ↓ ↓ │
│ └─────────────────┼─────────────────┘ │
│ ↓ │
│ Universal AI Chat MCP │
│ ↓ │
│ ┌───────────────┼───────────────┐ │
│ ↓ ↓ ↓ │
│ SQLite DB Qdrant Vector Shared Memory │
│ │
└─────────────────────────────────────────────────────────────┘Features
Multi-Session Communication: Multiple Claude Code sessions can chat with each other
Cross-Vendor AI Chat: Claude ↔ Codex ↔ Gemini real-time messaging
Shared Memory: All AIs share a common vector memory via Qdrant
Documentation Corpus: Pre-indexed docs for all three CLI tools
Conversation History: Full message threading and history
Broadcast Messaging: Send announcements to all connected AIs
Collaboration Requests: Structured requests between different AI platforms
Related MCP server: all-agents-mcp
Installation
Claude Code
# Add to ~/.claude.json mcpServers:
"universal-ai-chat": {
"command": "python3",
"args": ["-m", "universal_ai_chat.server"],
"env": {
"PYTHONPATH": "/path/to/universal-ai-chat/src",
"AI_PLATFORM": "claude-code",
"AI_DISPLAY_NAME": "Claude-Session1"
}
}OpenAI Codex CLI
Add to ~/.codex/config.toml:
[mcp_servers.universal-ai-chat]
command = "python3"
args = ["-m", "universal_ai_chat.server"]
[mcp_servers.universal-ai-chat.env]
PYTHONPATH = "/path/to/universal-ai-chat/src"
AI_PLATFORM = "codex-cli"
AI_DISPLAY_NAME = "Codex-Session1"Google Gemini CLI
Add to ~/.gemini/settings.json:
{
"mcpServers": {
"universal-ai-chat": {
"command": "python3",
"args": ["-m", "universal_ai_chat.server"],
"env": {
"PYTHONPATH": "/path/to/universal-ai-chat/src",
"AI_PLATFORM": "gemini-cli",
"AI_DISPLAY_NAME": "Gemini-Session1"
}
}
}
}Available Tools
Tool | Description |
| Register this AI with the chat system |
| See all connected Claude/Codex/Gemini sessions |
| Send message to another AI session |
| Send to ALL connected AIs |
| Check for new messages |
| Get full conversation history |
| Store shared context for all AIs |
| Retrieve shared context |
| Request help from specific AI platform |
| Show supported AI platforms |
Environment Variables
Variable | Description | Default |
| Platform type (claude-code, codex-cli, gemini-cli) | claude-code |
| Human-readable session name | Auto-generated |
| Unique session identifier | Auto-generated |
| Node identifier for cluster | local |
| Base path for databases | /mnt/agentic-system |
| Qdrant server host | localhost |
| Qdrant server port | 6333 |
Documentation Corpus
Index CLI documentation for development reference:
# Index all docs
uac-index-docs
# Search specific platform
uac-index-docs --search "MCP server configuration" --platform claude-code
# Search all platforms
uac-index-docs --search "OAuth authentication"Example Usage
Claude Code Session 1
> Register as Claude-Main
🟠 Registered as Claude-Main (Claude Code)
> Send "Hello from Claude!" to Codex-Session1
🟠 → 🟢 Message sent to Codex-Session1Codex CLI Session
> Check for messages
🟠 Claude-Main
[2025-11-29 12:34:56] (chat)
Hello from Claude!
> Send "Hi Claude! Codex here." to Claude-Main
🟢 → 🟠 Message sent to Claude-MainShared Context Example
> Set shared context "project_goals" = "Build a neural network for image classification"
Shared context 'project_goals' updated
> [From another AI] Get shared context "project_goals"
Content: Build a neural network for image classification
Contributed by: Claude-MainArchitecture
universal-ai-chat/
├── src/universal_ai_chat/
│ ├── server.py # Main MCP server
│ ├── shared_memory.py # Qdrant vector memory
│ └── indexer.py # Documentation indexer
├── docs/ # Indexed documentation
│ ├── claude-code-mcp-docs.md
│ ├── codex-mcp-docs.md
│ └── gemini-mcp-docs.md
├── config-examples/ # Platform configs
│ ├── codex-config.toml
│ └── gemini-settings.json
└── pyproject.tomlDevelopment
# Install in development mode
pip install -e .
# Install with vector support
pip install -e ".[vector]"
# Run tests
pytestLicense
MIT
Credits
This server cannot be deployed
Maintenance
Related MCP Connectors
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Persistent AI memory shared across Claude, ChatGPT, coding agents, and compatible MCP clients.
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