Contextberg
Contextberg is a privacy-first local memory app for AI agents that records screen activity, inputs, browser history and agent conversations to provide contextual memory to agents (e.g., coding agents) and to summarize recent work for quick resumption.
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Best for: Software & Gaming
What it does
AI Tools software for decision-makers comparing workflow fit and alternatives.
Best fit
Software & Gaming
Pricing snapshot
Pricing available on request
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Contextberg
Contextberg is a desktop application (macOS & Windows) that observes your work in the background—screenshots, inputs, browsing and agent conversations—and converts that activity into structured context that AI agents can consume. It is designed to act as long-term and short-term memory for agents (including coding agents) by distilling daily activity into activity memories, daily summaries, and long-term memory of frequently used tools and patterns. The product emphasizes privacy by storing work history locally and allowing users to choose inference destinations (local models, LM Studio, Codex, OpenRouter, Contextberg Cloud, etc.). It also includes an MCP server to connect compatible agents directly without additional configuration.
Turn your work into private memory for AI agents Discussion | Link
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Claim this listing for $29Key Features
Automatic context capture
Continuously records screen contents, user inputs, browser history and agent conversations in the background and makes them available to connected agents.
Three memory types
Generates activity memories (detailed logs of actions), daily memories (date-aggregated progress), and long-term memories (frequently used tools and patterns) for agent inference.
Privacy-first storage and model routing
Work history is stored locally by default; users can choose where to send inference requests (local model/LM Studio, Codex sign-in, Gemini/OpenRouter API key, Contextberg Cloud).
MCP server & agent integrations
Includes a built-in MCP server to connect supported agents (e.g., Claude Code, Cursor, OpenClaw, GitHub Copilot) without extra configuration.
Resume & summarization
When returning to work, Contextberg auto-summarizes recent activity (activity, browser, and agent history) so agents can immediately continue from where you left off; points of interest can be explored via chat.
Easy installation and no account required
Two-click install with no account or cloud lock-in required for local-only operation.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
Coding with context-aware agents
Provide coding agents with full contextual history (screenshots, terminal logs, prior agent interactions) so they can operate without repeatedly asking for state or filenames.
Resume interrupted work quickly
Automatically generate summaries of recent activity so users and agents can pick up work immediately after returning from a break.
Long-term agent memory for workflows
Maintain long-term memory of frequently used tools and behavioral patterns to improve agent relevance over time.
Privacy-first experimentation
Run local models or select specific inference routes when working with sensitive or private data while keeping raw work history on-device.
Integrations
Claude Code
Supported coding agent that can consume Contextberg-provided context.
Cursor
Supported agent whose history Contextberg can record and feed.
OpenClaw
Agent integration listed as supported for context feeding.
GitHub Copilot / Codex
Support for recording and routing context to Codex/GitHub Copilot (Codex sign-in mentioned).
LM Studio / Local models
Option to use fully local models (LM Studio) so inference stays on-device.
OpenRouter / Gemini (API keys)
Can route inference to OpenRouter or Gemini via user-provided API keys.
Contextberg Cloud
Cloud inference route option (optional; not required).
Benefits
Limitations
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Download and install the Contextberg desktop app (macOS or Windows).
- 2 Launch the app and connect a supported agent via the built-in MCP server or choose a model route (local model, LM Studio, Codex sign-in, Gemini/OpenRouter, Contextberg Cloud).
- 3 Work as usual: Contextberg will record activity in the background and begin generating activity, daily, and long-term memories; use the summary/chat features to resume or explore context.
Support
docs
Help center and documentation pages referenced on the site (サポート / ヘルプセンター).
blog
Product updates and launch posts available on the blog linked from the site.
social
Follow Contextberg on X (Twitter) as listed in the site footer.
API
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