Arun-kc/schemabrain

Overview

Schemabrain acts as a read-only intermediary between AI agents and databases, using a semantic knowledge graph to provide context and an audit log for transparency. It is built as an MCP-native tool in Python, enabling agents to query structured data without write access.

Best for

Best for
Developers building AI agents that need safe, contextual database access

Use cases

• Querying databases with natural language through AI agents
• Enforcing read-only access for agent interactions
• Auditing agent queries with a semantic context layer

Notes

Schemabrain acts as a read-only intermediary between AI agents and databases, using a semantic knowledge graph to provide context and an audit log for transparency. It is built as an MCP-native tool in Python, enabling agents to query structured data without write access.

8 stars on GitHub. Last updated 2026-06-18. Licensed Apache-2.0.

Use cases

• Querying databases with natural language through AI agents
• Enforcing read-only access for agent interactions
• Auditing agent queries with a semantic context layer

Pros

• Read-only architecture prevents accidental data modification
• Semantic knowledge graph improves query accuracy
• MCP-native design integrates with existing agent frameworks

Cons

• Limited to read-only operations, no write support
• Requires setup of semantic knowledge graph
• Relatively new project with small community (8 stars)

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.