Local Coder MCP Agent

This project packages a local coding agent workflow:

1. A Qwen coding model runs locally behind an OpenAI-compatible /v1/chat/completions API.
2. A Python worker talks to that local API with the OpenAI SDK.
3. A local-coder MCP server exposes delegate_to_local_coder to Codex.
4. Codex delegates implementation tasks to the local worker, then reviews tests and diffs itself.

No model weights are included. Use your own local model directory through MODEL_DIR.

Architecture

Codex
  -> MCP tool: delegate_to_local_coder(task, workspace, max_steps)
    -> mcp_servers.local_coder.server
      -> workers.coding.worker.CodingWorker
        -> OpenAI-compatible local model server
        -> restricted file/test/git tools inside the requested workspace

The worker can list files, read files, write files, patch exact text, run pytest, run a small allowlist of commands, search text, inspect git status, and inspect git diff. It refuses paths outside the selected workspace.

Install

git clone <your-repo-url>
cd local-coder-mcp-agent
python -m venv .venv
source .venv/bin/activate
python -m pip install -U pip
python -m pip install -e ".[dev,mlx]"
cp .env.example .env

Edit .env:

MODEL_DIR=${HOME}/models/Qwen3-Coder-30B-A3B-Instruct-4bit
ALLOWED_WORKSPACE_ROOT=${HOME}/AI/projects
LOCAL_CODER_BASE_URL=http://127.0.0.1:8080/v1
LOCAL_CODER_MODEL=default_model
LOCAL_CODER_API_KEY=local

ALLOWED_WORKSPACE_ROOT is the directory tree the worker is allowed to edit. For multiple roots, use ALLOWED_WORKSPACE_ROOTS separated by : on macOS/Linux.

Start The Model Server

For an MLX model on Apple Silicon:

source .venv/bin/activate
./scripts/start_qwen3_coder_server.sh

The script starts:

python -m mlx_lm.server \
  --model "${MODEL_DIR}" \
  --host 127.0.0.1 \
  --port 8080 \
  --max-tokens 4096 \
  --temp 0

Any OpenAI-compatible server works if it exposes http://127.0.0.1:8080/v1/chat/completions, or if you update LOCAL_CODER_BASE_URL.

Start The MCP Server Manually

source .venv/bin/activate
./scripts/start_local_coder_mcp.sh

Normally Codex starts the MCP server for you from config.toml.

Configure Codex MCP

Copy the local-coder block from config.example.toml into your Codex config.toml, then replace placeholders with local values:

[mcp_servers.local-coder]
enabled = true
command = "${PROJECT_ROOT}/.venv/bin/python"
args = ["-m", "mcp_servers.local_coder.server"]
cwd = "${PROJECT_ROOT}"

[mcp_servers.local-coder.env]
LOCAL_CODER_BASE_URL = "http://127.0.0.1:8080/v1"
LOCAL_CODER_MODEL = "default_model"
LOCAL_CODER_API_KEY = "local"
ALLOWED_WORKSPACE_ROOT = "${ALLOWED_WORKSPACE_ROOT}"

Use real local paths only in your private Codex config, never in committed files.

Delegate A Task From Codex

Example prompt to Codex:

Use the local-coder MCP server and specifically call delegate_to_local_coder.

Workspace:
${ALLOWED_WORKSPACE_ROOT}/sandbox

Task:
Add multiply(a: int, b: int) -> int to calculator.py.

Requirements:
- Do not change add(), subtract(), or divide().
- Add pytest coverage for multiply().
- Run all tests.
- Inspect git diff before finishing.

After the local worker completes the task, review its changes yourself.
Do not implement the change yourself unless the local worker fails.

The included examples/sandbox folder is a tiny pytest project for smoke tests.

Common Errors

Workspace is not inside an allowed root

Set ALLOWED_WORKSPACE_ROOT or ALLOWED_WORKSPACE_ROOTS so the requested workspace is inside an approved directory. This is intentional: the worker should not be allowed to edit arbitrary local files.

Worker exceeded maximum number of steps

Increase max_steps for larger tasks, or split the task into smaller steps. Good local-worker tasks are specific and verifiable.

Model returned no usable text

The local model server returned a response without usable content, reasoning_content, reasoning, or thinking. Try:

• Confirm the server implements OpenAI-compatible chat completions.
• Set LOCAL_CODER_ENABLE_THINKING=false.
• Reduce task size.
• Test the server with a direct /v1/chat/completions request.

Connection failed

Confirm the model server is running, the port matches LOCAL_CODER_BASE_URL, and no firewall or proxy is intercepting localhost traffic.

Security Notes

• Do not commit .env, private Codex config files, model weights, logs, keys, or generated caches.
• Keep ALLOWED_WORKSPACE_ROOT narrow.
• The local worker can edit and run limited commands inside allowed workspaces; review every diff before accepting changes.
• Keep the API server bound to 127.0.0.1 unless you have a separate network security plan.
• This repository intentionally uses placeholders such as ${HOME}, ${MODEL_DIR}, ${PROJECT_ROOT}, and ${ALLOWED_WORKSPACE_ROOT}.

Run Checks

python -m pytest -q
python -m py_compile \
  mcp_servers/local_coder/server.py \
  workers/coding/client.py \
  workers/coding/parser.py \
  workers/coding/tools.py \
  workers/coding/worker.py