BigQuery
This BigQuery MCP server, developed by LucasHild, provides a streamlined interface for language models to interact with Google BigQuery databases. It enables AI agents to inspect database schemas, list tables, and execute SQL queries using the BigQuery dialect. The server is configurable with project ID, location, and optional dataset filtering. By leveraging BigQuery's powerful data warehousing capabilities, it allows AI systems to analyze large datasets efficiently. This implementation is particularly useful for AI assistants designed to perform data analysis tasks, generate insights from business intelligence data, or automate reporting processes using BigQuery as the backend data source.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/lucashild/mcp-server-bigquery
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve BigQuery from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.