Knowledge Base

Store project documentation in the cloud. The AI retrieves relevant chunks during generation, ensuring output aligns with your team's conventions.

Cloud Documents

Documents are chunked and indexed for semantic search. Each document:

  • Belongs to a team and optionally a project
  • Has a name, content, and metadata
  • Is searched automatically during generation based on spec + query context

Operations (via Remote MCP)

OperationMCP Tool
Uploadremote_ingest_cloud_document
Searchremote_cloud_search
Listremote_list_cloud_documents
Getremote_get_cloud_document
Updateremote_update_cloud_document
Deleteremote_delete_cloud_document
Remote MCP
curl -X POST "https://api.aexol.ai/mcp" \
  -H "Authorization: Bearer sk-aexol-team-..." \
  -d '{
    "jsonrpc": "2.0", "id": 1, "method": "tools/call",
    "params": {
      "name": "remote_ingest_cloud_document",
      "arguments": {
  "name": "api-design.md",
  "content": "# API Design Guidelines\n\nAll endpoints use REST..."
}
    }
  }'

AI Retrieval Flow

Specification
Your .aexol file
Parse to AST
Syntax tree
AI Generation
Model + KB context
Output Code
TS, Python, Rust, Go, JS

Generated code follows your team's conventions, API patterns, and naming standards without explicit prompting.

Permissions

Admin
  • Full control
  • Settings & billing
  • Manage members
  • All projects
  • Full KB access
Moderator
  • Manage projects/members
  • Read + Write KB
  • Can't change settings
  • Can't manage billing
Member
  • Access shared projects
  • Generate code
  • Read-only KB
  • No project management

What to Upload

Good knowledge documents:

  • API specifications, database schemas
  • Coding standards, naming conventions
  • Product requirements, domain knowledge
  • Plain text or Markdown works best

Next Steps