Library/arcanaForked

aidancorrell/arcana

arcana

Agent-first data catalog. MCP server that gives AI agents the context to write correct SQL — semantic search, auto-documentation, lineage-aware retrieval, and a self-improving feedback loop.

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Builder

aidancorrell

aidancorrell • individual

Stars

Using upstream star count

Forks

Using upstream fork count

Open Issues

Activity Score

0/100

0 commits in 30d

Created

Mar 19, 2026

Project creation date

README Summary

Arcana is an agent-first data catalog built as an MCP (Model Context Protocol) server that provides AI agents with the necessary context to write correct SQL queries. It features semantic search capabilities, automatic documentation generation, lineage-aware data retrieval, and incorporates a self-improving feedback loop to enhance query accuracy over time.

AI Dev Skills

Unmapped

Retrieval-Augmented GenerationSemantic SearchAgent Architecture DesignModel Context Protocol IntegrationKnowledge Graph ConstructionData Lineage TrackingNatural Language to SQLVector-based Information RetrievalAuto-documentation GenerationFeedback Loop OptimizationSQL Query GenerationAgent OrchestrationSchema UnderstandingFeedback Loop DesignInformation RetrievalAgentic AI SystemsContext-Aware Prompt Engineering

Taxonomy

AI Trends

Agentic AI Compound AI Systems Model Context Protocol Tool Use and Function Calling Retrieval-Augmented Generation Model Context Protocol (MCP)Tool-augmented AI

Deployment Context

Self-hosted On-premise Cloud API

Industries

Developer Tools Data Engineering Analytics Platforms Analytics

Modalities

Text Code Tabular

Skill Areas

Retrieval-Augmented Generation Semantic Search Agent Architecture Design Model Context Protocol Integration Knowledge Graph Construction Data Lineage Tracking Natural Language to SQL Vector-based Information Retrieval Auto-documentation Generation Feedback Loop Optimization SQL Query Generation Agent Orchestration Schema Understanding Feedback Loop Design Information Retrieval Agentic AI Systems Context-Aware Prompt Engineering

Use Cases

AI-assisted SQL query generation Semantic database search Automated data documentation Data lineage and impact analysis Database schema understanding for LLMs Self-improving data catalog systems SQL query generation from natural language SQL Query Generation from Natural Language Database Schema Discovery and Documentation Data Lineage and Impact Analysis Semantic Search over Database Metadata Self-improving Data Context through Feedback Loops Automated data catalog documentation Data lineage discovery and tracking Schema semantic search AI agent context augmentation for database queries Self-improving query accuracy through feedback

Recent Activity

Updated 19 days ago

7 Days

30 Days

90 Days

Quality

beta

Quality: medium
Maturity: beta

PM Skills

Product DiscoveryUser Experience

Languages

Rust100.0%

Timeline

Project created: Mar 19, 2026
Forked: Mar 26, 2026
Your last push: 19 days ago
Upstream last push: 19 days ago
Tracked since: Mar 26, 2026

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