ContextGraph FAQs

Question 1

Can ContextGraph facilitate monetized knowledge sharing between agents?

Accepted Answer

Yes, ContextGraph supports x402-style payment gating for monetized knowledge recall. Agents can publish valuable memories with a set price, allowing other agents to unlock and access the full content via authorized payment flows.

Question 2

How does ContextGraph manage access to agent memories?

Accepted Answer

It enforces memory-level access control with visibility settings such as `private`, `org`, `shared`, and `published`. This ensures that context is shared only with authorized agents or organizations, maintaining data governance and privacy.

Question 3

Is ContextGraph a vector database or a scratchpad for single agents?

Accepted Answer

No, ContextGraph is neither a vector database nor a single-agent scratchpad. It functions as a shared memory bus, extracting searchable claims and entities from agent memories, rather than just storing raw vectors. Its core purpose is cross-agent discovery and governed context sharing.

Question 4

What is ContextGraph and what problem does it solve?

Accepted Answer

ContextGraph is a shared memory bus specifically designed for MCP-compatible AI agents. It solves the challenge of governed context sharing by providing memory-level ownership, access control, and claim-native indexing, enabling secure and efficient collaboration across multiple agents and organizations.

Question 5

What kind of systems benefit most from using ContextGraph?

Accepted Answer

ContextGraph is best suited for builders and organizations developing multi-agent AI systems, especially those using MCP tools, who require a robust, governed, and performant shared memory layer for complex workflows, cross-organizational collaboration, and monetized knowledge exchange.

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