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BigQuery
Google's own hosted BigQuery MCP server — explore datasets and run SQL under IAM, with a read-only tool by default.
Quick answer
What it does
Exposes six tools over a Google-hosted HTTP endpoint: list_dataset_ids, get_dataset_info, list_table_ids, get_table_info, execute_sql_readonly (SELECT only), and execute_sql (any statement). Every query it runs carries the job label `goog-mcp-server: true` and is billed to the project you name in the call.
Best for
- Schema and dataset exploration
- Analytical query drafting
- BigQuery ML evaluation and prediction from chat
- IAM-governed agent access with audit logs
Not for
- Result sets over 3,000 rows
- Queries that run longer than three minutes
Source: top-mcps.com/mcp/bigquery — verified Sep 2026
Setup recipe
Pick your client, then follow the three steps.
- 1
Install
claude_desktop_config.jsonjson{ "mcpServers": { "bigquery": { "command": "npx", "args": [ "-y", "mcp-remote", "https://bigquery.googleapis.com/mcp" ] } } }Claude Desktop launches stdio servers, so mcp-remote bridges to the hosted endpoint and opens the sign-in in your browser. On Pro, Max, Team and Enterprise you can skip the file: Settings → Connectors → Add custom connector → https://bigquery.googleapis.com/mcp. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
CLI or .mcp.jsonshellclaude mcp add --transport http bigquery https://bigquery.googleapis.com/mcpThen run /mcp inside Claude Code to finish the sign-in. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
.cursor/mcp.jsonjson{ "mcpServers": { "bigquery": { "url": "https://bigquery.googleapis.com/mcp" } } }Global path: ~/.cursor/mcp.json. Cursor shows "Needs login" once it connects — click it to authorize. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
.vscode/mcp.jsonjsonc{ "servers": { "bigquery": { "type": "http", "url": "https://bigquery.googleapis.com/mcp" } } }VS Code uses the "servers" key. Run MCP: List Servers → Start Server and allow the sign-in. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
~/.codeium/windsurf/mcp_config.jsonjson{ "mcpServers": { "bigquery": { "serverUrl": "https://bigquery.googleapis.com/mcp" } } }Windsurf uses "serverUrl" for hosted servers. Open via Cascade → hammer icon → Configure. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
cline_mcp_settings.jsonjson{ "mcpServers": { "bigquery": { "command": "npx", "args": [ "-y", "mcp-remote", "https://bigquery.googleapis.com/mcp" ] } } }Bridged through mcp-remote. Open via the Cline sidebar → MCP Servers → Edit. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
~/.continue/config.jsonjson{ "experimental": { "modelContextProtocolServers": [ { "transport": { "type": "streamable-http", "url": "https://bigquery.googleapis.com/mcp" } } ] } }Continue takes the hosted URL directly in the transport block. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
CLIshellcodex mcp add bigquery --url https://bigquery.googleapis.com/mcpCodex detects OAuth support and opens the browser to authorize. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
~/.config/zed/settings.jsonjsonc{ "context_servers": { "bigquery": { "command": { "path": "npx", "args": [ "-y", "mcp-remote", "https://bigquery.googleapis.com/mcp" ] } } } }Bridged through mcp-remote under "context_servers". Settings live-reload on save. Authorization happens in the browser on first use (OAuth); no token goes in the config file.
ChatGPT → Settings → Connectors (remote URL)json{ "name": "BigQuery", "transport": "http", "url": "https://bigquery.googleapis.com/mcp" }Paste this into Settings → Connectors → Add custom connector. Requires ChatGPT Pro / Team / Enterprise / Edu with Developer mode enabled.
- 2
Set required secrets
No credentials required — this MCP runs over stdio without authentication.
- 3
Try a minimum working prompt
Minimum working prompt pending verification. Try any prompt from the MCP’s README once installed.
Tools & permissions
| Tool | Description | Args | Side effects |
|---|---|---|---|
list_dataset_ids | List BigQuery dataset IDs in a Google Cloud project, with pagination. | projectId: string | Read |
get_dataset_info | Get metadata about a BigQuery dataset. | projectId: string, datasetId: string | Read |
list_table_ids | List table IDs in a BigQuery dataset, with pagination. | projectId: string, datasetId: string | Read |
get_table_info | Get metadata about a BigQuery table. | projectId: string, datasetId: string, tableId: string | Read |
execute_sql_readonly | Run a read-only SQL query. Restricted to SELECT — INSERT, UPDATE, DELETE and stored procedures are rejected. | projectId: string, query: string | Read |
execute_sql | Run any SQL statement BigQuery supports, including DDL, DML and BigQuery ML functions. | projectId: string, query: string | Write |
Security & scope
- Access scope
- Read + write
- Sandbox
- Hosted by Google at bigquery.googleapis.com/mcp. Authorisation is OAuth 2.0 with the https://www.googleapis.com/auth/bigquery scope resolving to a Google Cloud identity, so every call is evaluated against that principal's IAM roles and recorded in Cloud Audit Logs. No local process runs and no service-account key is stored on the client.
- Gotchas
- execute_sql can run DDL and DML — DROP TABLE and DELETE included. The read-only variant is a preference expressed to the model, not an enforcement boundary; bound the risk with IAM by granting only dataViewer.
- BigQuery is billed per byte scanned and this server has no dry-run tool, so a broad SELECT the agent writes is charged in full.
- Results are capped at 3,000 rows and queries at three minutes, so a wide query returns a silently partial answer rather than an error.
- Queries are billed to the projectId passed in each call, which need not be the project the agent is nominally working in — check the project a tool call names before approving it.
Agent prompt pack
— copy into Claude, Cursor, or ChatGPT.Recommend the best MCP servers for [task: e.g. databases work] in [client: Claude]. Constraints: - Prefer tools that are [official | open-source | read-only] — pick what matters for my use case. - Exclude MCPs that require [e.g. a paid plan, OAuth-only flows, remote-only transport]. - Return at most 3 picks, ranked. For each pick include: 1. One-sentence rationale. 2. The ready-to-paste install snippet for my client. 3. Any required secrets I need to create before installing. Cross-check the top-mcps.com listing: https://top-mcps.com/top-mcps-for-databases
Compare BigQuery MCP vs [Google MCP Toolbox MCP] for the following job: [describe the job, e.g. "let an agent create GitHub issues on bug triage"]. Judge them on: - Setup time and complexity (what a new user hits first). - Auth model (none / API key / OAuth 2.1) and credential risk. - Transport (stdio / Streamable HTTP / SSE) and where the server runs. - Required secrets and the blast radius if they leak. - Operational risk in an unattended agent loop. - Which one is "good enough" for a weekend prototype vs. production. End with one sentence: which should I pick for my scenario, which is: [my scenario]. References: - https://top-mcps.com/mcp/bigquery - top-mcps.com listing for Google MCP Toolbox
Install the BigQuery MCP server for my [client: Claude] at the default config path for that client. Use the exact install snippet published at https://top-mcps.com/mcp/bigquery (fetch https://top-mcps.com/mcp/bigquery.json for the canonical server.json if you can read URLs). Before finishing: 1. Create the required secrets (no secrets) and put them in the appropriate env block — do not hard-code them. 2. Restart or reload the client so it picks up the new server. 3. Verify the server is connected (green / running state) and at least one tool is listed. 4. If anything fails, read the client's MCP logs and report the exact error — do not silently retry. Confirm when done and list the tools the server now exposes.
Frequently asked questions
What changed
— 2 updates tracked.Refreshed install snippets and fact sheet; verified for 2026.
Initial directory listing.
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