Contextberg
Summary
Contextberg turns your work into AI agent memory, served over the Model Context Protocol (MCP).
Similar Articles
ContextsBase - Memory for your Agents
ContextsBase is a context infrastructure for coding agents, offering features, business rules, data model, tests, and design over MCP, compatible with Claude, Cursor, or Copilot.
@swyx: explain this
This article explains the Model Context Protocol (MCP) for building pluggable AI agent architectures, detailing lessons from building an MCP server at Sentry, including OAuth 2.1 integration, designing agent-friendly tool interfaces, and current ecosystem limitations.
Code execution with MCP: Building more efficient agents
This article from Anthropic explores how integrating code execution with the Model Context Protocol (MCP) can improve the efficiency of AI agents. It addresses challenges like token overload from tool definitions and intermediate results, proposing code execution as a solution to reduce latency and costs.
Agentic Context Management: Memory and Cost as Architecture Problems
This paper argues that managing context in AI agents should be treated as a lifecycle architecture problem, proposing Agentic Context Management (ACM) with five primitives and a reference implementation that achieves high benchmark scores.
@sourcebot_dev: Give agents context across your entire codebase. Open source, 1 min install.
Sourcebot has launched an open-source MCP (Model Context Protocol) server that connects AI coding agents like Cursor, Claude Code, and Copilot to an entire codebase for search, file reading, and reference resolution. It supports OAuth 2.0 and API key authorization with a quick 1-minute install.