ai-sync 0.1.10

Self-contained AI config sync for Codex, Cursor, and Gemini.

ai-sync

A self-contained local config store for Codex, Cursor, and Gemini CLI. Define agents, skills, MCP servers, and client settings once in ~/.ai-sync/, then sync them to every client with one command.

License: PolyForm Noncommercial 1.0.0 (non-commercial use only).

Overview

This repo provides:

• The ai-sync CLI – Manage ~/.ai-sync/ and run syncs
• Agents – Sub-agents derived from prompts with per-client metadata
• Skills – Agent Skills (SKILL.md) mirrored to all clients
• Rules/commands – Prompt snippets/shortcuts mirrored to each client’s equivalent feature
• MCP servers – Model Context Protocol servers with centralized config and secrets
• Client configuration – Generic settings (subagents, mode) derived into client-specific configs
• OAuth token portability – Manual copy of client OAuth caches across machines (automated capture/restore planned)

All syncing is idempotent: identical targets cause no writes; changed targets overwrite in place.

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Install

End users (recommended)

pipx install ai-sync

Local development

poetry sync --with dev

Optional (task runner):

brew install just
just install
just test
just release 0.1.4

Quick start

ai-sync setup --op-account NAME
ai-sync import --repo /path/to/config-repo   # optional
ai-sync sync

Prerequisites

• Python 3.11+
• Codex, Cursor, and/or Gemini CLI installed
• 1Password Desktop app (for OP_ACCOUNT) or OP_SERVICE_ACCOUNT_TOKEN for service accounts
• For MCP stdio servers: Node.js (npx), uv (uvx for workspace-mcp), pip install mcp-server-fetch for fetch

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Project structure

This repo ships the sync tool. Runtime data lives in ~/.ai-sync/.

Repo:
.
├── src/
│   └── ai_sync/               # Python: ai-sync
│       └── .client-versions.json  # Supported client versions (packaged)
├── tests/
├── pyproject.toml
└── README.md

Runtime:
~/.ai-sync/
├── config.toml                # op_account, secret_provider
├── .env.tpl                   # MCP secrets (op:// refs resolved via 1Password)
├── config/
│   ├── prompts/
│   ├── skills/
│   ├── rules/
│   ├── mcp-servers.yaml
│   └── client-settings.yaml
└── cache/

Import repo layout:

<repo>/
├── prompts/
├── skills/
├── mcp-servers.yaml
├── client-settings.yaml
├── .env.tpl            # optional
└── rules/              # optional

---

ai-sync

Usage

ai-sync setup --op-account NAME
ai-sync import --repo /path/to/config-repo   # optional
ai-sync sync

Running ai-sync with no subcommand defaults to sync. Other commands: ai-sync setup, ai-sync import, ai-sync doctor.

Sync options

Option	Description
(none)	Full sync: agents → skills → rules → MCP servers → client config
--force	Update the packaged client version lock (dev-only), then sync
--no-interactive	Skip interactive prompts
--plain	Plain output (implies --no-interactive)
--override / --override-json	Override manifest leaf values (e.g. /servers/context7/enabled=false)

Sync order

1. Agents – From ~/.ai-sync/config/prompts/*.md → ~/.codex/agents/, ~/.cursor/agents/, ~/.gemini/agents/
2. Skills – From ~/.ai-sync/config/skills/*/ → ~/.codex/skills/, ~/.cursor/skills/, ~/.gemini/skills/
3. Rules – From ~/.ai-sync/config/rules/ → client rule/command locations
4. MCP servers – From ~/.ai-sync/config/mcp-servers.yaml → client MCP configs, MCP instructions
5. Client config – From ~/.ai-sync/config/client-settings.yaml → approval policy, sandbox, features

Sync strategy

• Agents, skills, rules, client config: Files overwritten if they exist. Untracked agents/skills/rules (not in ~/.ai-sync/config/prompts/, ~/.ai-sync/config/skills/, or ~/.ai-sync/config/rules/) are left alone.
• Client config: Deep-merge with existing; ai-tools keys overwrite on conflict.
• MCP servers: Merged with existing; managed servers updated, user-added servers preserved.

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Agents

Source structure

Each agent lives in ~/.ai-sync/config/prompts/:

~/.ai-sync/config/prompts/
├── <agent_name>.md           # Prompt content (required)
└── <agent_name>.metadata.yaml   # Optional metadata

Metadata schema (~/.ai-sync/config/prompts/<name>.metadata.yaml)

Metadata is generic (client-agnostic). The sync script adapts it per client.

Key	Description	Default
slug	Agent ID (kebab-case)	Derived from filename
name	Display name	From filename
description	Short description	Extracted from prompt

Untracked agents (in client but not in ~/.ai-sync/config/prompts/) are left alone.

Target layout per client

Client	Target
Codex	~/.codex/agents/<slug>/prompt.md + config.toml
Cursor	~/.cursor/agents/<slug>.md (frontmatter)
Gemini	~/.gemini/agents/<slug>.md (frontmatter)

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Skills

Skills are directories under ~/.ai-sync/config/skills/ with a SKILL.md file. The sync script mirrors each skill to all three clients.

Structure

~/.ai-sync/config/skills/
└── <skill-name>/
    ├── SKILL.md          # Required
    ├── reference.md      # Optional
    ├── examples.md       # Optional
    └── scripts/          # Optional; copied if present

Paths containing .venv, node_modules, __pycache__, .git, or .DS_Store are skipped. Untracked skills (in client but not in ~/.ai-sync/config/skills/) are left alone.

Targets

• ~/.codex/skills/<skill-name>/
• ~/.cursor/skills/<skill-name>/
• ~/.gemini/skills/<skill-name>/

---

MCP servers

Manifest (~/.ai-sync/config/mcp-servers.yaml)

servers:
  <server_id>:
    method: stdio | http | sse
    command: npx
    args: ["-y", "@modelcontextprotocol/server-xxx"]
    enabled: true
    clients: [codex, cursor, gemini]   # Optional; default: all
    timeout_seconds: 60               # Optional; startup/tool timeout (seconds)
    trust: true                        # Optional; Cursor/Gemini: auto-approve tools

STDIO servers – command, args; env vars use "${VAR}" refs resolved from ~/.ai-sync/.env.tpl.

HTTP/SSE servers – url, httpUrl; optional bearer_token_env_var for Codex.

HTTP with OAuth – httpUrl + oauth.enabled: true; clientId/clientSecret from ~/.ai-sync/.env.tpl via "${VAR}":

  google-maps-grounding-lite:
    method: http
    httpUrl: https://mapstools.googleapis.com/mcp
    oauth:
      enabled: true
      clientId: "${GOOGLE_MAPS_GROUNDING_LITE_CLIENT_ID}"
      clientSecret: "${GOOGLE_MAPS_GROUNDING_LITE_CLIENT_SECRET}"

Configured servers

Server	Method	Description
context7	stdio	Documentation lookup (@upstash/context7-mcp)
fetch	stdio	URL fetch → markdown (python -m mcp_server_fetch)
playwright	stdio	Browser control (@playwright/mcp)
exa	http	Search API
google-workspace-perso	stdio	Gmail, Calendar, Drive (personal @gmail.com, separate OAuth)
google-workspace-pro	stdio	Gmail, Calendar, Drive (work @sherpas.com, separate OAuth)
google-maps-grounding-lite	http	Maps grounding (OAuth)

Secrets (~/.ai-sync/.env.tpl)

All MCP secrets live in ~/.ai-sync/.env.tpl. Use op:// references for 1Password:

CONTEXT7_API_KEY=op://Private/AI Tools Secrets/CONTEXT7_API_KEY
EXA_API_KEY=op://Private/AI Tools Secrets/EXA_API_KEY
GOOGLE_OAUTH_CLIENT_ID_PERSO=op://Private/AI Tools Secrets/GOOGLE_OAUTH_CLIENT_ID_PERSO
...

In mcp-servers.yaml, reference them with "${VAR_NAME}" in each server's env or oauth block. The sync script resolves these at runtime via 1Password (requires OP_ACCOUNT or OP_SERVICE_ACCOUNT_TOKEN).

Requirements: 1Password Desktop app (for OP_ACCOUNT) or OP_SERVICE_ACCOUNT_TOKEN (service account).

Client targets

Client	Target	Strategy
Codex	~/.codex/config.toml [mcp_servers.<id>]	Merge
Codex	~/.codex/mcp.env	Bearer token exports (source before running Codex)
Cursor	~/.cursor/mcp.json	Overwrite mcpServers
Gemini	~/.gemini/settings.json mcpServers	Deep-merge

OAuth token portability

OAuth tokens are stored per client (e.g. ~/.gemini/mcp-oauth-tokens.json). To move them between machines, copy the client token files manually via a secure channel (rsync, 1Password, etc.). Automated capture/restore is planned.

---

Client configuration

Single YAML definition → derived into Codex, Gemini, and Cursor.

Schema (~/.ai-sync/config/client-settings.yaml)

Key	Values	Description
experimental	true | false	Enable experimental/preview features; suppress experimental warnings where supported
subagents	true | false	Enable multi-agents, sub-agents, child-prompts, AGENTS.md
mode	strict | normal | yolo	Approval / restriction mode (default: normal)
tools.sandbox	true | false	Gemini only. When false, allow MCP tools filesystem access (uvx, etc.)

Mode semantics

Mode	Meaning
strict	Most restrictive: read-only where supported; approval required for actions
normal	More permissive; allow reads/writes while still requiring approval for destructive actions where supported
yolo	No approval prompts, no restrictions (full access)

Client mapping (from official docs)

Generic	Codex	Gemini	Cursor
subagents: true	features.multi_agent, features.child_agents_md	experimental.enableAgents	—
experimental: true	suppress_unstable_features_warning	experimental.plan	—
tools.sandbox: false	—	tools.sandbox	—
mode: strict	approval_policy=on-request, sandbox_mode=read-only	general.defaultApprovalMode=plan, tools.sandbox=true	permissions: {allow:[], deny:[]}
mode: normal	approval_policy=untrusted, sandbox_mode=danger-full-access	general.defaultApprovalMode=auto_edit, tools.sandbox=false	allow: [Shell(*), Read(*), Write(*), WebFetch(*), Mcp(*:*)]
mode: yolo	approval_policy=never, sandbox_mode=danger-full-access	general.defaultApprovalMode=yolo, tools.sandbox=false	allow: [Shell(*), Read(*), Write(*), WebFetch(*), Mcp(*:*)]

Client targets

Client	Target	Strategy
Codex	~/.codex/config.toml	Deep-merge with existing; ai-tools keys overwrite. No backup.
Gemini	~/.gemini/settings.json	Deep-merge with existing; ai-tools keys overwrite. No backup.
Cursor	~/.cursor/cli-config.json	Deep-merge with existing; ai-tools keys overwrite. No backup.

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Dependencies

This project uses Poetry for dependency management and packaging:

poetry sync --with dev

Dependencies: pyyaml>=6.0, tomli>=2.0, tomli-w>=1.0, and others (see pyproject.toml).

Testing

poetry run pytest

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Packaging & Release

This project is published to PyPI as ai-sync.

Release checklist

1. Update README if anything changed in CLI behavior or setup.
2. Run the release:

just release X.Y.Z

This runs ./scripts/release_checks.sh, poetry lock, bumps the version, runs tests, commits, tags, and pushes.

3. GitHub Actions runs tests, builds artifacts, publishes to PyPI, and creates a GitHub Release.

Notes

• Use pipx install ai-sync for end users.
• Keep ai-sync as the only supported CLI name.

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.gitignore

If you maintain a separate config repo for ai-sync import, consider ignoring:

• config/mcp-servers.yaml
• config/client-settings.yaml
• .env.tpl
• knowledge-base/*
• .env, Python bytecode, virtual envs, .pytest_cache/, node_modules/, .DS_Store, etc.

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Workflow summary

New machine setup

1. Clone repo (tooling only)
2. poetry sync --with dev
3. ai-sync setup --op-account NAME (or set OP_SERVICE_ACCOUNT_TOKEN)
4. ai-sync import --repo /path/to/config-repo (optional)
5. Ensure ~/.ai-sync/.env.tpl has correct 1Password refs
6. ai-sync sync
7. For Codex HTTP MCP servers: source ~/.codex/mcp.env in shell profile

Adding an MCP server

1. Edit ~/.ai-sync/config/mcp-servers.yaml
2. Add required vars to ~/.ai-sync/.env.tpl (use op:// refs for secrets)
3. Run ai-sync sync

Adding an agent

1. Add ~/.ai-sync/config/prompts/<name>.md
2. (Optional) Add ~/.ai-sync/config/prompts/<name>.metadata.yaml
3. Run ai-sync sync

Adding a skill

1. Create ~/.ai-sync/config/skills/<skill-name>/SKILL.md
2. Run ai-sync sync

Changing client mode

1. Edit ~/.ai-sync/config/client-settings.yaml (subagents, mode)
2. Run ai-sync sync

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References

• Codex config reference
• Codex security & sandbox
• Gemini CLI configuration
• Cursor CLI permissions
• Agent Skills standard