From multi-agent-config
Manage multi-agent AI code configurations across platforms (OpenAI Codex, Claude Code, Cursor, Gemini). Use when: (1) initializing new multi-agent projects, (2) syncing configurations (MCP servers, skills, rules, subagents) across platforms, (3) translating configurations between different agent platforms, (4) migrating from one agent platform to another, or (5) maintaining consistent agent configurations across development teams using different tools.
npx claudepluginhub marsolab/skills --plugin multi-agent-configThis skill uses the workspace's default tool permissions.
Manage and sync AI code agent configurations across OpenAI Codex, Claude Code,
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Manage and sync AI code agent configurations across OpenAI Codex, Claude Code, Cursor, and Gemini.
This skill enables you to maintain consistent AI agent configurations across multiple platforms. It handles translation between different configuration formats (TOML ↔ JSON), directory structures, and platform-specific conventions.
Supported platforms:
python scripts/init_project.py /path/to/project
This creates:
.agent-config/ - Shared source of truth.codex/ - Codex-specific structure.claude/ - Claude Code-specific structure.cursor/ - Cursor-specific structure# Sync all configurations to all platforms
python scripts/sync_config.py --to all
# Sync to specific platform
python scripts/sync_config.py --to claude-code
# Sync only MCP servers
python scripts/sync_config.py --mcp-only --to codex
When to use: Starting a new project that will be used with multiple AI code agents.
Process:
Example:
# Initialize project
python scripts/init_project.py ./my-project
# Edit shared configuration
cd my-project
vim .agent-config/rules.md
vim .agent-config/mcp-servers.json
# Sync to all platforms
python scripts/sync_config.py --to all
When to use: After editing shared configs or when switching between agent platforms.
What gets synced:
Sync options:
# All configurations to all platforms
python scripts/sync_config.py --to all
# Specific platform
python scripts/sync_config.py --to codex
python scripts/sync_config.py --to claude-code
# Specific config type
python scripts/sync_config.py --mcp-only
python scripts/sync_config.py --rules-only
python scripts/sync_config.py --skills-only
python scripts/sync_config.py --agents-only
Process:
.agent-config/mcp-servers.jsonExample MCP server config:
{
"servers": {
"context7": {
"command": "npx",
"args": ["-y", "@upstash/context7-mcp"],
"env": {},
"enabled": true,
"description": "Developer documentation MCP"
}
}
}
Process:
.agent-config/skills/Example:
# Create skill directory
mkdir -p .agent-config/skills/my-skill
# Create SKILL.md
cat > .agent-config/skills/my-skill/SKILL.md << 'EOF'
---
name: my-skill
description: Description of when to use this skill
---
# My Skill
Instructions for using this skill.
EOF
# Sync to platforms
python scripts/sync_config.py --skills-only
When to use: Migrating from one platform to another or understanding config differences.
Platform reference docs:
references/codex.md - Codex configuration formatreferences/claude-code.md - Claude Code configurationreferences/cursor.md - Cursor format (partial)references/translation-mappings.md - Cross-platform mappingsreferences/docker-mcp-gateway.md - Docker MCP GatewayManual translation example:
from scripts.translate_utils import ConfigTranslator, load_toml, save_json
# Load Codex config
codex_config = load_toml('~/.codex/config.toml')
# Translate MCP servers
translator = ConfigTranslator()
claude_mcp = translator.toml_mcp_to_json(codex_config)
# Save to Claude Code config
save_json(claude_mcp, '.claude/config.json')
When to use: Want centralized MCP management with better security and isolation.
Benefits:
Migration process:
# 1. Migrate existing MCP servers to Docker MCP Gateway
python scripts/sync_config.py --migrate-to-docker-mcp
# 2. Follow generated instructions in DOCKER_MCP_SETUP.md
# This will show you exactly which docker commands to run
# 3. Example commands (generated by migration):
docker mcp catalog init
docker mcp server enable context7 github filesystem
docker mcp secret create context7-key "your-api-key"
docker mcp secret create github-token "ghp_token"
# 4. Configure servers
docker mcp config write 'servers:
filesystem:
config:
allowed_paths: ["/home/user/projects"]
context7:
env:
CONTEXT7_API_KEY: secret://context7-key'
# 5. Test the gateway
docker mcp tools ls
Result: All your AI clients now use a single gateway instead of individual MCP servers.
Before (traditional):
# Codex config - managing individual servers
[mcp_servers.context7]
command = "npx"
args = ["-y", "@upstash/context7-mcp"]
env = { API_KEY = "exposed-in-config" }
[mcp_servers.github]
command = "npx"
args = ["-y", "@modelcontextprotocol/server-github"]
env = { GITHUB_TOKEN = "exposed-in-config" }
After (Docker MCP Gateway):
# Codex config - single gateway
[mcp_servers.docker-gateway]
command = "docker"
args = ["mcp", "gateway", "run"]
All MCP configuration now managed through Docker MCP CLI:
docker mcp server ls # List enabled servers
docker mcp secret ls # List secrets (secure)
docker mcp config read # View configuration
# Initialize shared project config
python scripts/init_project.py ~/team-project
# Edit shared rules
vim ~/team-project/.agent-config/rules.md
# Sync to all platforms
cd ~/team-project
python scripts/sync_config.py --to all
# Currently using Codex, want to try Claude Code
cd ~/my-codex-project
# Initialize Claude Code structure
python scripts/init_project.py . --platforms claude-code
# Copy Codex config to shared
cp AGENTS.md .agent-config/rules.md
# Sync to Claude Code
python scripts/sync_config.py --to claude-code
# Step 1: Migrate existing MCP servers to Docker MCP Gateway
cd ~/my-project
python scripts/sync_config.py --migrate-to-docker-mcp
# This generates DOCKER_MCP_SETUP.md with specific commands for your setup
# Example output:
# Step 2: Initialize Docker MCP
docker mcp catalog init
# Step 3: Enable your MCP servers
docker mcp server enable context7 github filesystem
# Step 4: Store secrets securely
docker mcp secret create context7-key "sk-..."
docker mcp secret create github-token "ghp_..."
# Step 5: Configure servers
docker mcp config write 'servers:
context7:
env:
CONTEXT7_API_KEY: secret://context7-key
github:
env:
GITHUB_TOKEN: secret://github-token
filesystem:
config:
allowed_paths:
- /home/user/projects'
# Step 6: Test the gateway
docker mcp tools ls
docker mcp tools call read_file '{"path": "README.md"}'
# Step 7: Your client configs are already updated!
# All AI clients now use the Docker MCP Gateway
Benefits of Docker MCP Gateway:
# Option 1: stdio (default) - one gateway per client
# Each client starts its own gateway process
# No additional setup needed
# Option 2: SSE - shared gateway for all clients
# Start gateway once
docker mcp gateway run --port 8080 --transport sse
# Update client configs to use shared gateway
cat > ~/.codex/config.toml << EOF
[mcp_servers.docker-gateway]
url = "http://localhost:8080"
EOF
cat > ~/.claude/config.json << EOF
{
"mcpServers": {
"docker-gateway": {
"url": "http://localhost:8080",
"transport": "sse"
}
}
}
EOF
# Option 3: streaming - high-performance shared gateway
docker mcp gateway run --port 8080 --transport streaming
For detailed platform formats and translations:
references/codex.md - OpenAI Codex configurationreferences/claude-code.md - Claude Code configurationreferences/cursor.md - Cursor configuration (partial)references/gemini.md - Gemini configuration (placeholder)references/docker-mcp-gateway.md - Docker MCP Gateway (recommended)references/translation-mappings.md - Cross-platform mappings