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

Dimensionmcp-knowledge-graphPersistent memory for AI models through a local knowledge graph.ChEMBL MCP ServerUnofficial MCP server providing advanced access to the ChEMBL chemical database
FMRS56 / 100 · C75 / 100 · B
Reliability7 / 2012 / 20
Security and permissions11 / 2016 / 20
Maintenance8 / 2014 / 20
Documentation16 / 2018 / 20
Setup experience14 / 2015 / 20
Best for
  • Claude users who need persistent memory across conversations
  • Developers who want local persistent memory in their projects
  • Users concerned about data privacy and prefer local storage over cloud
  • 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 distributed or high-concurrency storage
  • Advanced security needs like built-in encryption or access control
  • Users who wish to store memory files in the cloud managed by a service provider
  • 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 and write to the local file system (within specified --memory-path or project .aim directory)
  • Run npx commands to start the server
  • 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
  • Local files might be accidentally deleted or overwritten (the system has _aim marker protection, but risk remains)
  • Sensitive information stored locally could be exposed if not encrypted
  • Dependency on Node.js version and npm package management may cause conflicts
  • 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
Tools1027