MCP for Engineering Teams
Shared configurations, security best practices, and governance patterns for team MCP adoption
Why Teams Need a MCP Strategy
When one developer uses MCP, it's a productivity boost. When an entire team does, it becomes infrastructure. Without coordination, you get inconsistent configurations, security risks, and duplicated effort. Here's how to do it right.
Step 1: Create a Shared MCP Config
Version-control your MCP configurations alongside your code. Use environment variables for secrets — never hardcode tokens in config files.
// .cursor/mcp.json (or .claude.json) — committed to git
{
"mcpServers": {
"github": {
"command": "npx",
"args": ["@modelcontextprotocol/server-github"],
"env": { "GITHUB_TOKEN": "${GITHUB_TOKEN}" }
},
"postgres-staging": {
"command": "npx",
"args": ["@modelcontextprotocol/server-postgres"],
"env": { "DATABASE_URL": "${STAGING_DATABASE_URL}" }
}
}
}
// Each developer sets their own tokens in .env.local (gitignored)Step 2: Define Access Tiers
Tier 1: Read-Only
Default for all developers. Database MCP in read-only mode, filesystem limited to project files.
Tier 2: Read-Write Dev
For senior developers. Write access to staging databases, GitHub PR creation.
Tier 3: Admin
Team leads only. Production database access, infrastructure MCP servers, deployment tools.
Step 3: Combine with Team AI Skills
Pair your shared MCP config with team-wide AI Skills to ensure everyone's AI assistant follows the same coding standards:
project-root/
├── .cursor/
│ ├── mcp.json # Shared MCP servers
│ └── rules/
│ ├── architecture.mdc # Team architecture rules
│ ├── testing.mdc # Testing conventions
│ └── security.mdc # Security requirements
├── .claude/
│ ├── settings.json # Claude Code MCP config
│ └── skills/
│ ├── code-review/SKILL.md
│ └── database-migration/SKILL.md
└── .env.local # Personal API tokens (gitignored)Security Checklist for Teams
Set Up MCP for Your Team
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