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DimensionBigQuery MCP ServerSecure, read-only access to BigQuery for LLMs.ChEMBL MCP ServerUnofficial MCP server providing advanced access to the ChEMBL chemical database
FMRS62 / 100 · C75 / 100 · B
Reliability8 / 2012 / 20
Security and permissions16 / 2016 / 20
Maintenance10 / 2014 / 20
Documentation15 / 2018 / 20
Setup experience13 / 2015 / 20
Best for
  • Developers and analysts who want to query BigQuery quickly via AI assistants
  • Organizations that need to prevent AI agents from modifying data
  • Environments with sensitive data that require field-level access restrictions
  • Drug discovery and computational chemistry researchers
  • Bioinformatics teams needing ChEMBL data through AI assistants
  • Developers comfortable with Node.js or Docker
Not for
  • Scenarios requiring write, update, or delete operations
  • Users who need unrestricted access to all columns
  • Strict security environments that cannot tolerate data leaving the network (since results are sent to LLM providers)
  • Production settings requiring official ChEMBL support (this is unofficial)
  • Users without a Node.js or Docker environment
  • General database tasks unrelated to ChEMBL
Required permissions
  • BigQuery read permissions (e.g., roles/bigquery.user or roles/bigquery.dataViewer)
  • For service account auth, access to the service account key file
  • For advanced features, permission to list datasets and tables, and run dry-run queries
  • Outbound network access to https://www.ebi.ac.uk/chembl/api/data
  • Read-only access to public API data; no authentication credentials required
Risks and side effects
  • Data exfiltration: query results are sent to LLM providers (Anthropic, OpenAI) and may leave your network
  • Despite field restrictions, AI agents may attempt to infer data through crafted queries
  • Misconfiguration may weaken restrictions, e.g., incorrectly setting preventedFields or maximum bytes billed
  • Unofficial project with license marked NOASSERTION (README claims MIT); verify licensing yourself
  • Data accuracy depends on the ChEMBL REST API and the server's parsing may contain defects
  • 30-second request timeouts may constrain large batch queries
  • README inconsistency on tool count (22 vs 27) raises documentation reliability concerns
Supported clientsClaude Desktop, Claude CodeClaude Desktop
Tools027