Hermes Local Agent Lanes

Safe local-model support lanes for a cloud owner agent.

This project packages a pattern we use with Hermes Agent: keep the strongest cloud model as the owner that makes decisions, mutates files, verifies, and reports; route low-risk background work to fast local models through narrow MCP tools.

Local models should be useful coworkers, not unsupervised operators.

What this repo shows

• Local MLX model as a safe MCP support lane for a cloud owner agent.
• SSH stdio MCP mounting so another computer can use the local model without exposing a LAN HTTP port.
• Support-only boundary guards: summary/classification/critique/draft are allowed; shell/patch/git/deploy/config/cron/hook/secrets are blocked.
• Owner router demo for deciding task intensity and whether support models may be used.
• Separate quota support lane pattern for using a secondary coding model as an advisory reviewer/patch-sketcher while the owner agent applies and verifies changes.

Architecture

Cloud owner agent (Hermes / GPT-class model)
  ├─ owns architecture, mutations, tests, commits, final QC
  ├─ calls narrow local MCP support tools when useful
  │
  └─ Local support lanes
      ├─ MLX/OpenAI-compatible model server on localhost
      ├─ stdio MCP wrapper: support + health tools only
      ├─ optional SSH stdio mount from another computer
      └─ optional coding support lane in read-only/advisory mode

Why this matters

Most local-agent demos fail in one of two ways:

1. They let a weaker local model execute risky actions.
2. They use the expensive frontier model for every low-value summarization or log-reading step.

This repo uses a stricter split:

Layer	Allowed	Forbidden
Cloud owner	plan, decide, edit, test, commit, report	surprise paid/external actions
Local MCP support	summarize, classify, critique, draft, explain	shell, patch, git, deploy, config, cron, hooks, secrets
Secondary coding quota lane	read-only review, patch sketches, bug hypotheses	direct workspace mutation unless owner verifies

Quick start

1. Run a local OpenAI-compatible model server

Any local server with /v1/chat/completions works. Example environment variables:

export LOCAL_MODEL_BASE_URL="http://127.0.0.1:18085/v1/chat/completions"
export LOCAL_MODEL_NAME="your-local-mlx-model"

2. Start the MCP server locally

python3 -m hermes_local_agent_lanes.mcp_support_server

3. Mount it from a local MCP client

{
  "mcpServers": {
    "local-support-lane": {
      "command": "python3",
      "args": ["-m", "hermes_local_agent_lanes.mcp_support_server"]
    }
  }
}

4. Mount it from another computer over SSH

This avoids exposing the model server to your LAN:

{
  "mcpServers": {
    "local-support-lane": {
      "command": "ssh",
      "args": [
        "user@your-mac-or-workstation",
        "cd /path/to/hermes-local-agent-lanes && python3 -m hermes_local_agent_lanes.mcp_support_server"
      ]
    }
  }
}

Tools exposed

local_support

Ask the local model for low-risk support only:

• summary
• classification
• critique
• draft
• simple code explanation
• read-only long-context compression

Risky prompts are blocked before reaching the model and return:

TASK_REQUIRES_OWNER_AGENT

local_support_health

Checks whether the local model endpoint is reachable.

Run tests

python3 -m unittest discover -s tests

The tests exercise JSON-RPC MCP initialize/tool listing and the hard boundary guard without requiring a real model.

Repo status

This is a small pattern repo, not a full Hermes fork. It is intentionally portable and public-safe: no private paths, no credentials, no runtime databases, no model weights.

See also

• docs/architecture.md — deeper design notes
• examples/mcp-config-ssh.json — remote MCP mount example
• examples/owner-router-demo.json — intensity-routing example
• src/hermes_local_agent_lanes/owner_router.py — small callable router demo

License

MIT