> For the complete documentation index, see [llms.txt](https://docs.dctx.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.dctx.ai/key-components/context-graph-layer/features.md).

# Features

#### 1. **Interconnected Context**

All individual data points (identity, behavior, governance, history) are interlinked, forming a complete picture of an entity’s role and evolution in Web3.

#### 2. **Real-Time Querying**

Agents and dApps can perform graph-based queries like:

* “Who are the most active DAOs this user is involved with?”
* “What other users share similar staking behavior?”

#### 3. **Schema-Driven**

Every relationship and data field in the graph is derived from DMCP-defined schemas, ensuring consistency and interoperability.

#### 4. **Temporal Awareness**

Context Graphs are **time-aware** — meaning they can reflect how entities or relationships evolve over time.

#### 5. **Composable for AI**

LLMs or AI agents can consume subgraphs as contextual input for reasoning, decision-making, and interactions.