The real catalog of tools for AI agents

Convert JSON samples into TypeScript interfaces and Zod schemas, with inference caveats.

OPC UA companion spec types, namespace dependencies, and engineering units for AI agents

JSON Schema, TypeScript types, mocks for AI agents

Knowledge graph ingestion, entity search, ontology analysis, and CoPass scoring.

Knowledge graph ingestion, entity search, ontology analysis, and CoSync scoring.

Build, manage, and run AI workflow automations with Typenode.

Ontology-based MCP server for database schema analysis and RDF/OWL ontology generation

Multi-LLM entity enrichment: schemas, single/batch enrichment, fusion, model benchmarks.

Web, academic and code search with graph RAG, data lineage, ontology and cross-project schema links.

Design database schemas from natural language, validate SQL, generate migrations and types

Read-only MCP server for exposing database schema metadata without row data.

Draw and edit Neo4j graph data models in toro4n: nodes, relationships, properties, constraints.

Reads a migration, Prisma schema, Django model or TypeORM entity and marks every column a subject ac

The AI that understands raw data: Schema over your tables and databases, as MCP tools.

Read and write one codebase ontology kept as Markdown in the repository.

Ontology platform for field service: AI agents observe, connect and act on business objects.

Connect to your Supabase database to query data and schemas.

A label property graph on SQLite/Postgres with multi-ontology routing and a gated MCP server.

data: URL media-type shape, value discarded

PostgreSQL, MySQL, OpenAPI/Swagger, and shared Agent Memory with scoped access.