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Give AI agents an executable context layer for accurate data querying.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ktx" yet — see the docs or source repo.
Use ktx to configure a semantic layer for an AI agent, connect our orders and customers tables, and define reusable skills so the agent can answer “What were last month’s sales and repeat purchase rates by region?” while avoiding incorrect field usage.
A semantic-layer and skill configuration that lets the AI answer business data questions accurately using standardized definitions.
Design a memory system with ktx for an analytics agent that stores common metric definitions, team conventions, and past query context, so the agent consistently uses shared definitions like “active users” and “net revenue,” and explain how to expose these capabilities through MCP.
A plan covering memory strategy, context management, and MCP integration so the agent can analyze consistently over time.
Explain how to use ktx so Claude Code or Codex can securely access an analytics database through MCP, including skill design, permission boundaries, query flow, and an example task such as querying key metrics for a weekly report.
An integration guide showing how agents can securely query data, invoke skills, and complete analytics tasks.
Access KTalk recordings, transcripts, and summaries inside Claude Code.
Enables fast, safe file operations and bounded edits for coding workflows.
Build persistent knowledge graphs for AI workflows with git-aware project context.
Compress, route, remember, and verify AI coding context with major token savings.
Give AI agents persistent project memory with searchable code and decisions.
Search, validate, and cross-reference structured Markdown knowledge vaults for AI workflows.