Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.memorycrystal.ai/llms.txt

Use this file to discover all available pages before exploring further.

If memory is what your AI learns from talking to you, a Knowledge Base is the shelf of books you hand it on purpose.

​
What this means in practice

Knowledge Bases are best for stable reference material such as:
  • docs
  • policies
  • runbooks
  • imported project notes
  • scoped reference data for a team, agent, or workspace
They are meant to sit beside conversational memory, not replace it.

​
How it actually works

The main implementation and HTTP surfaces live in:
  • convex/crystal/knowledgeBases.ts
  • convex/crystal/knowledgeHttp.ts
  • packages/mcp-server/README.md
  • convex/schema.ts
Knowledge Base operations include listing, creating, importing, querying, and background enrichment/backfill flows.

​
Commands / examples

Representative tool names:
  • crystal_list_knowledge_bases
  • crystal_query_knowledge_base
  • crystal_import_knowledge
Representative endpoints:
  • GET /api/knowledge-bases
  • POST /api/knowledge-bases/:knowledgeBaseId/import
  • POST /api/knowledge-bases/:knowledgeBaseId/query

​
Common mistakes

  • treating Knowledge Bases as just another name for memory stores
  • mixing mutable conversational memories and stable reference imports together conceptually
  • documenting import/query flows without tying them to the actual HTTP/tool surface

​
Source of truth

Primary files behind this page:
  • convex/crystal/knowledgeBases.ts
  • convex/crystal/knowledgeHttp.ts
  • packages/mcp-server/README.md
  • convex/schema.ts