qualixar/slm-mesh

Peer-to-peer communication for AI coding agents — now across machines.
> Part of the Qualixar research initiative by Varun Pratap Bhardwaj.
> SLM stands for SuperLocalMemory — the local-first AI memory system. SLM Mesh is the communication layer that wires AI agent sessions together.
Your AI sessions can finally talk to each other.
https://github.com/user-attachments/assets/1016ec92-8d71-4570-89a8-3e512850557c
> 3 AI agents across VS Code, iTerm2, and Antigravity — discovering each other, sharing state, and coordinating in real-time.
## The Problem
Every developer running parallel AI coding sessions hits the same wall: sessions are completely isolated. Session A fixes a database race condition. Session B is building a feature that touches the same database. Session B has no idea what Session A just did.
You become the message bus — copy-pasting context between terminals, losing time, losing focus.
This is not a Claude Code problem. This is not a Cursor problem. This is an AI agent architecture problem. Every tool — Claude Code, Cursor, Windsurf, Aider, Codex — has isolated sessions. SLM Mesh fixes that.
## Quick Start
bash
# Install
npm install -g slm-mesh
# Add to Claude Code
claude mcp add --scope user slm-mesh -- npx slm-mesh
# Optional: Add slash commands (works in every project)
mkdir -p ~/.claude/commands
cp $(npm root -g)/slm-mesh/skills/.md ~/.claude/commands/
# Now type /mesh-peers, /mesh-send, /mesh-lock, /mesh-status, /mesh-sync in any session
Zero config. Zero cloud. Zero dangerous flags. Works with any MCP-compatible AI coding agent.
## No Dangerous Flags Required
Some tools require --dangerously-skip-permissions to work. SLM Mesh does not. It runs entirely on localhost with bearer token authentication. No network exposure. No elevated permissions. No flags to explain to your security team.
## How It Works
Developer starts AI agent session
→ Agent spawns SLM Mesh MCP server (stdio)
→ MCP server auto-starts broker on localhost (if not running)
→ MCP server registers with broker, gets peer ID
→ Broker opens Unix Domain Socket for real-time push ( "message"
slm-mesh broadcast "message"
# Shared State
slm-mesh state set key value
slm-mesh state get key
# Locks
slm-mesh lock list
# Events
slm-mesh events
# JSON mode (for scripts)
slm-mesh status --json
slm-mesh peers --json
## Python Client
bash
pip install slm-mesh
python
from slmmesh import SLMMeshClient
client = SLMMeshClient()
peers = client.peers()
client.send(myid, peers[0].id, "What are you working on?")
The Python client wraps the broker HTTP API. Zero dependencies (stdlib only). The broker must be running (auto-started by any MCP connection or slm-mesh start).
## Architecture
┌─────────────────────────────────────────────────────┐
│ SLM Mesh v1.0.0 │
│ │
│ ┌──────────────┐ ┌───────────────────────────┐ │
│ │ Broker │ │ MCP Server (per session) │ │
│ │ (auto-start) │◄───►│ 8 tools for AI agents │ │
│ │ localhost │ │ Registers with broker │ │
│ │ SQLite + UDS │ │ Receives push via UDS │ │
│ └──────────────┘ └───────────────────────────┘ │
│ ▲ │
│ │ ┌───────────────────────────┐ │
│ └─────────────►│ CLI (standalone) │ │
│ │ slm-mesh peers/send/... │ │
│ └───────────────────────────┘ │