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DimensionSLayerAn embeddable, expressive semantic layer for AI agents and humansMCP ClickHouseConnect ClickHouse to your AI assistantsChEMBL MCP ServerUnofficial MCP server providing advanced access to the ChEMBL chemical database
FMRS48 / 100 · D79 / 100 · B75 / 100 · B
Reliability7 / 2012 / 2012 / 20
Security and permissions9 / 2018 / 2016 / 20
Maintenance10 / 2017 / 2014 / 20
Documentation10 / 2017 / 2018 / 20
Setup experience12 / 2015 / 2015 / 20
Best for
  • Data teams wanting a governed data access surface for AI agents
  • Developers building analytical MCP servers or APIs on top of a warehouse
  • Teams with existing dbt, Cube, or Ossie semantic configs they want to reuse
  • Engineers embedding a semantic layer into Python apps
  • Teams already using ClickHouse who want AI assistants to access data directly.
  • Scenarios requiring fast, read-only data queries and schema exploration.
  • 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 access to the database (SLayer connections are read-only)
  • Simple cases where direct SQL is sufficient and no semantic layer is needed
  • Non-Python stacks that cannot run the CLI or an MCP subprocess
  • Scenarios requiring write access to the database without explicit opt-in.
  • Production environments with stringent security requirements that avoid default permission settings.
  • 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
  • Read-only database access to configured datasources
  • Environment variables holding database credentials such as DB_PASSWORD
  • Permission to run the local CLI and the MCP subprocess
  • Permission to modify Claude Code MCP configuration
  • Requires read-only access to ClickHouse database (default).
  • Optional: write access via CLICKHOUSE_ALLOW_WRITE_ACCESS.
  • Optional: destructive operations via CLICKHOUSE_ALLOW_DROP.
  • 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
  • Database credentials are passed to the MCP subprocess via environment variables, so a compromised launching shell could expose them
  • Connections are read-only but can still read sensitive business data, so row-level security should be applied
  • Once connected via MCP, agents can run queries, so verify their query scope matches expectations
  • As a third-party project, availability and behavior depend on upstream maintenance
  • If write access is enabled, AI might make unintended modifications.
  • If DROP access is enabled, data deletion could occur accidentally.
  • Credentials may be exposed via environment variables.
  • 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 CodeClaude DesktopClaude Desktop
Tools0427