On-Premise Deployment

Context7 On-Premise lets you run the full Context7 stack inside your own infrastructure. Your code, documentation, and embeddings never leave your environment.

What's Included

• Full Context7 parsing and indexing pipeline
• Local vector storage (no external vector DB required)
• Built-in MCP server. Works with any MCP-compatible AI client
• Web UI for managing indexed libraries and configuration
• REST API compatible with the public Context7 API
• Private GitHub and GitLab repository ingestion

Setup

Go to context7.com/plans and click On-Premise Trial. Fill out the request form. No credit card required. You'll receive a 30-day full-featured license key via email once approved.

Follow the deployment guide for your platform:

Open http://localhost:3000 in your browser. On first launch, the setup wizard guides you through configuring:

1. AI Provider - Choose OpenAI, Anthropic, Gemini, or a custom OpenAI-compatible endpoint. Enter your API key and model name.
2. Embedding Provider - Use the same provider as your LLM, or configure a separate one for embeddings.
3. Git Tokens - Add a GitHub and/or GitLab token for the platforms you use.

All configuration is stored locally in the embedded database and can be updated later from the Settings page.

From the dashboard, click Add Repository and enter a GitHub or GitLab URL. Once ingestion completes, your private docs are ready to query.

You can also add libraries via the REST API:

curl -X POST http://localhost:3000/api/parse \
  -H "Content-Type: application/json" \
  -d '{"url": "https://github.com/your-org/your-repo"}'

Connecting Your AI Client

Point your MCP client at your deployment URL. Replace https://context7.internal.yourcompany.com with your actual host.

Claude Code

claude mcp add --scope user --transport http context7 https://context7.internal.yourcompany.com/mcp

Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "context7": {
      "url": "https://context7.internal.yourcompany.com/mcp"
    }
  }
}

Opencode

{
  "mcp": {
    "context7": {
      "type": "remote",
      "url": "https://context7.internal.yourcompany.com/mcp",
      "enabled": true
    }
  }
}

For other clients, see All Clients.

Configuration

Environment Variables

These are set in your docker-compose.yml or .env file before starting the container.

AI Provider Settings

Configured via the Settings page in the web UI.

Examples

Embedding Settings

By default, Context7 uses the same provider as your LLM for generating embeddings. You can configure a separate embedding provider if needed.

Git Access Tokens

Configured via the Settings page in the web UI.

You only need tokens for the platforms you use. If you only parse GitLab repos, you don't need a GitHub token, and vice versa. Create tokens with repo scope (GitHub) or read_repository scope (GitLab) for private repository access.

Access Control

Admin credentials are set during first login (default: admin / admin). Change these immediately after setup via Settings > Change Credentials.

The Settings page lets you control which operations are available without authentication.

When a permission is off, the operation requires admin login. The MCP endpoint and search API are always publicly accessible.

Web UI

Open your deployment URL in a browser to access the dashboard. From here you can:

• Add and remove libraries
• Trigger re-indexing
• Monitor parsing status and logs
• Update AI provider settings, git tokens, and permissions
• Test MCP connectivity
• Change admin credentials

Operations

For updating, health checks, and other operational tasks, see the deployment guide for your platform:

• Docker Operations
• Kubernetes Operations

Support

For license issues, upgrade requests, or deployment questions, contact [email protected].