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Compare scores, permissions, risks, and fit in one decision-focused table.

DimensionIBM i MCP ServerMCP server for IBM i systems, providing secure SQL-based access.ChEMBL MCP ServerUnofficial MCP server providing advanced access to the ChEMBL chemical database
FMRS42 / 100 · D75 / 100 · B
Reliability5 / 2012 / 20
Security and permissions6 / 2016 / 20
Maintenance7 / 2014 / 20
Documentation13 / 2018 / 20
Setup experience11 / 2015 / 20
Best for
  • Building AI agents or AI-powered applications that interact with IBM i.
  • Requiring remote server support over the MCP protocol (stdio or HTTP).
  • Leveraging Mapepire for fast, lightweight, low-latency database access.
  • Defining custom SQL tools via YAML.
  • Drug discovery and computational chemistry researchers
  • Bioinformatics teams needing ChEMBL data through AI assistants
  • Developers comfortable with Node.js or Docker
Not for
  • Terminal-first interactions without an MCP client; the `ibmi` CLI is better for that.
  • IBM i systems without Mapepire installed.
  • Scenarios requiring traditional ODBC/JDBC database access.
  • Simple SQL query tools without AI or MCP integration.
  • 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
  • Requires IBM i credentials (username and password) for database access.
  • Requires Mapepire server running on IBM i (default port 8076).
  • May require network access to the specified port on the IBM i system.
  • Needs access to QSYS2 system views and tables for the example tools.
  • 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
  • Credential management: passing passwords directly can be risky; use environment variables or secure storage.
  • Network attack surface: exposing the MCP server over HTTP could allow unauthorized access unless secured (HTTPS, authentication).
  • Data exposure: SQL tools may access sensitive data; restrict tool scope.
  • Resource consumption: long-running queries may impact IBM i performance.
  • 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, VSCode Copilot, BobClaude Desktop
Tools127