Context FAQs

Question 1

What is Context?

Accepted Answer

Context is a Model Context Protocol (MCP) server that exposes context resolution functionalities to AI agents using JSON-RPC 2.0 over stdio, acting as a primary integration surface for agent frameworks.

Question 2

How does Context enhance AI agent capabilities?

Accepted Answer

It enables AI agents to efficiently resolve specific context from caches based on queries and token budgets, ensuring they have access to relevant information for decision-making and tasks within their LLM applications.

Question 3

What communication protocol does Context use?

Accepted Answer

Context communicates via JSON-RPC 2.0 over standard input/output (stdio), adhering to the Model Context Protocol (MCP) for seamless integration with client applications and agent frameworks.

Question 4

How can I configure the Context server?

Accepted Answer

The server is easily configured using environment variables, such as `CONTEXT_CACHE_ROOT` to specify the root directory for context caches and `CONTEXT_TOOL_TIMEOUT_SECS` for operation timeouts, offering deployment flexibility.

Question 5

What cache management functionalities does Context offer?

Accepted Answer

Context provides tools to resolve context from caches using queries, list all available context caches under the server's root directory, and inspect cache metadata and validity for proper management and oversight.

Context

Context

Key Features

Use Cases

Key Features

Use Cases