Context Graph Python Packages

neo4j-agent-memory

A graph-native memory system for AI agents and context graphs. Store conversations, build knowledge graphs, and let your agents learn from their own reasoning — all backed by Neo4j.

trustgraph-base

The Semantic Intelligence Layer for Ontologies

trustgraph-embeddings-hf

The Semantic Intelligence Layer for Ontologies

trustgraph-flow

The Semantic Intelligence Layer for Ontologies

trustgraph-cli

The Semantic Intelligence Layer for Ontologies

trustgraph

The Semantic Intelligence Layer for Ontologies

trustgraph-vertexai

The Semantic Intelligence Layer for Ontologies

trustgraph-bedrock

The Semantic Intelligence Layer for Ontologies

trustgraph-ocr

The Semantic Intelligence Layer for Ontologies

trustgraph-mcp

The Semantic Intelligence Layer for Ontologies

trustgraph-docling

The Semantic Intelligence Layer for Ontologies

trustgraph-unstructured

The Semantic Intelligence Layer for Ontologies

create-context-graph

AI agents with graph based reasoning memory, scaffolded in seconds

lerim

Compiles AI agent traces and truns them into reusable context.

trustgraph-parquet

Connect ontology-grounded context graphs with deterministic AI agent governance to enforce business rules before execution and preserve decision evidence.

potpie

Context Graph for AI Native SDLC

openmnemex

Agent memory for LLMs — a self-pruning knowledge context graph modeled on human memory. Long-term, navigable, context-budget-aware memory with no vector DB, no embeddings, no server. Markdown + git. Claude Code plugin.

iflow-mcp-trustgraph-ai-trustgraph-mcp

The Semantic Intelligence Layer for Ontologies

trellis-ai

Shared context substrate for AI agents. Retrieval that learns what's useful. Runs local or cloud.

agentlearn

Recursive learning framework, give any AI agent a self-improvement loop with memory. No fine-tuning, just API calls

tonggraph

Lightweight graph engine for AI graph context, memory, and agent harness with Rust Core.