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Side-by-side MCP evidence comparison
Evidence fieldGoogle BigQuery MCPShortlist candidateSupabase MCPMCP100 Recommended
Task fit
Best for
  • BigQuery exploration, metadata lookup, analytics, forecasting, and governed SQL workflows
  • Teams that can dedicate a least-privileged Google identity/project
  • Inspecting one Supabase project's schema, logs, advisors, and docs
  • Development environments using project-scoped read-only access
  • Teams that understand database and deployment consequences
Not ideal for
  • Production datasets without tight IAM and query-cost controls
  • Use cases that require a read-only guarantee but still expose execute_sql
  • Production database administration by an unattended agent
  • Users needing only public Supabase documentation
  • Organizations unable to grant Supabase OAuth access to an MCP client
Avoid when
  • The configured principal has broad project/dataset privileges
  • You cannot monitor audit logs, quotas, and query spend
  • The server would be left organization-wide rather than project-scoped
  • Write-capable SQL, migrations, functions, branches, or storage changes cannot be human-approved
  • Production secrets or customer records could be returned to the model
Provenance
Provenance details

First-party MCP

reviewed-detail:google-bigquery-mcp · Publisher source ↗

First-party MCP

Supabase · Publisher source ↗

Maintenance
Maintenance details

Repo: Not documented

Package: Not documented

Repo: Sep 24, 2026

Package: Sep 21, 2026

Popularity evidence
GitHub starsNot documented

2,919

GitHub stars · checked 2026-09-24T04:16:20.864000Z

Package downloads / 30 daysNo reliable download data

406,869

package downloads / 30 days · checked 2026-09-24T04:17:50.300000Z

Client coverage
Client coverage detailsNot documented
Claude Code✓ Streamable HTTP
Claude Desktop✓ Streamable HTTP
Codex✓ Streamable HTTP
VS Code✓ Streamable HTTP
Cursor✓ Streamable HTTP
OpenCode✓ Streamable HTTP
Client coverage noteLocal stdio runs on your computer. Streamable HTTP connects to a remotely hosted MCP server.
Access and data
AuthenticationUses Google Cloud authentication for the MCP Toolbox/BigQuery source; exact mechanism depends on the deployed toolbox environment.Hosted MCP uses browser OAuth and grants organization access to the MCP client. Project scope, read-only mode, and feature groups are encoded in URL query parameters. Enterprise-managed authentication is GA for eligible Team and Enterprise organizations. Access remains scoped to each user's existing Supabase role and permissions.
CostBigQuery query/storage charges and any infrastructure costs apply.The MCP server is open source; normal Supabase plan, database, branch, Edge Function, storage, and usage charges apply. Branching and some storage operations require a paid plan.
PermissionsBigQuery IAM controls accessible projects/datasets and operations. Use a dedicated least-privileged principal.Without project_ref the hosted server can access all projects in the authorized organization. With project_ref it is limited to one project. read_only=true uses a read-only Postgres user for SQL and disables listed mutation tools. Feature groups can further narrow exposed tools.
Data handlingThe server can inspect metadata and execute SQL against BigQuery; query results may contain sensitive warehouse data.Enabled tools may return schemas, table data from executed queries, logs, security/performance advisors, project metadata, publishable keys, types, and Edge Function source. Hosted mode sends tool requests through Supabase's MCP service.
Limitations
Tradeoffs
  • Strong first-party docs and IAM integrate well with enterprise Google Cloud controls
  • execute_sql makes the real safety boundary the configured identity and SQL policy, not the MCP layer itself
  • Project scoping removes account-level tools but materially reduces blast radius.
  • Read-only mode disables mutations but also removes migration, deployment, branch, and storage configuration workflows.
  • Branching and some storage capabilities require paid plans; the server is pre-1.0 and may change.
Risk contextHigh. SQL can expose data, incur large query cost, or perform DDL/DML if the identity permits it. Require IAM scoping, quotas, logs, and review.Unscoped or write-enabled access can affect every project in an organization, execute SQL, apply migrations, deploy functions, or manage branches. Always set project_ref and read_only=true first, minimize feature groups, and avoid production data.
Evidence date
Editorial review2026-09-112026-09-05
Candidate evidence2026-09-11T00:00:00.000Z2026-09-24T04:25:05.554391Z

Popularity, maintenance, fit, permissions, and client support are independent evidence fields.

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