RunContext
Allows connecting to ClickHouse databases, enabling AI agents to query and understand the schema through a semantic metadata layer.
Allows connecting to Databricks databases, enabling AI agents to query and understand the schema through a semantic metadata layer.
Allows connecting to DuckDB databases, enabling AI agents to query and understand the schema through a semantic metadata layer.
Allows connecting to MySQL databases, enabling AI agents to query and understand the schema through a semantic metadata layer.
Allows connecting to PostgreSQL databases, enabling AI agents to query and understand the schema through a semantic metadata layer.
Allows connecting to Snowflake databases, enabling AI agents to query and understand the schema through a semantic metadata layer.
Allows connecting to SQLite databases, enabling AI agents to query and understand the schema through a semantic metadata layer.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@RunContextsearch for customer orders"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Quick Start
npx @runcontext/cli setupA browser wizard opens. Connect your database, fill out the Context Brief, and RunContext scaffolds your semantic plane automatically.
Related MCP server: DataHub MCP Server
How It Works
The context setup wizard walks you through six steps:
Step | What happens |
1. Connect | Connect to your database |
2. Define | Name your semantic plane, set owner and sensitivity |
3. Scaffold | Auto-introspect schema and generate Bronze-tier metadata |
4. Checkpoint | Review what was built |
5. Curate | Hand off to your IDE's AI agent to curate metadata to Gold using real data queries |
6. Serve | Start the MCP server and serve your semantic plane to AI tools |
The result is a context/ directory of YAML files following the OSI (Open Semantic Interchange) specification.
Tiers
Bronze -- Scaffolded automatically. Every model and field has a description, owner, and type. Your data is discoverable.
Silver -- Sample values, tags, and richer descriptions. AI agents can interpret the data with confidence.
Gold -- Golden queries, guardrails, semantic roles, and business rules. Agents generate correct SQL on the first try.
Check your progress with context tier.
Commands
context setup # Browser wizard -- database to semantic plane
context tier [model] # Bronze/Silver/Gold scorecard
context serve # Start MCP server (stdio for IDE integration)
context lint # Validate metadata
context fix # Auto-fix lint issues
context verify # Check metadata against live database
context build # Compile context layer to manifest
context dev # Watch mode
context introspect # Schema introspection
context explain [term] # Look up models, terms, or ownersMCP Server
Add RunContext to your AI tool's MCP configuration:
{
"mcpServers": {
"runcontext": {
"command": "npx",
"args": ["@runcontext/cli", "serve", "--stdio"]
}
}
}6 MCP tools available:
Tool | Description |
| Find models, datasets, and fields by keyword |
| Get full model details |
| Run the linter |
| Get tier scorecard |
| Find validated SQL queries |
| Get WHERE clauses and access rules for tables |
Works with Claude Code, Cursor, Copilot, Windsurf, Claude Desktop, and any MCP-compatible tool.
Database Support
Database | Supported |
PostgreSQL | Yes |
DuckDB | Yes |
MySQL | Yes |
SQL Server | Yes |
SQLite | Yes |
Snowflake | Yes |
BigQuery | Yes |
ClickHouse | Yes |
Databricks | Yes |
Packages
Package | Description |
CLI, setup wizard, and MCP server | |
Compiler, linter, tier engine, adapters | |
MCP protocol implementation | |
Browser-based setup wizard and planes viewer | |
Design system components | |
Database utilities | |
Project scaffolder ( |
Links
License
MIT
This server cannot be deployed
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