Context Mode vs OzBrain: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Context Mode and OzBrain — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Context Mode

mksglu

Free

An MCP server that sandboxes tool output, persists session memory in SQLite, and enforces context routing across 17 AI coding platforms.

Sandboxed Tool Output: Tool results are executed and filtered outside the context window so only the answer returns to the model, cutting a 315 KB payload to about 5.4 KB.
SQLite Session Continuity: File edits, git operations, tasks, errors, and user decisions are tracked in SQLite so the agent can resume exactly where it left off after a compaction.
FTS5 + BM25 Retrieval: Session events are indexed into SQLite FTS5 and retrieved by BM25 relevance rather than being replayed wholesale into context.
Think-in-Code Routing: A mandatory paradigm across supported clients that has the model write a script to compute results instead of reading files into context, replacing many tool calls with one.
Hook-Based Enforcement: On Claude Code the plugin registers PreToolUse, PostToolUse, UserPromptSubmit, PreCompact, SessionStart, and Stop hooks so routing is injected at runtime with no file written to your project.
Eleven MCP Tools: Six sandbox tools (ctx_batch_execute, ctx_execute, ctx_execute_file, ctx_index, ctx_search, ctx_fetch_and_index) plus five meta tools for stats, diagnostics, upgrade, purge, and insight.
Persistent Knowledge Base: Local files and directories can be indexed into an FTS5 store and searched later, with a purge command to delete everything permanently.
Savings Diagnostics: ctx_stats reports per-tool context savings and token consumption while ctx_doctor validates runtimes, hooks, FTS5, and plugin registration.

Long Coding Sessions: Keep a multi-hour agent session usable by preventing large Playwright snapshots, issue lists, and logs from consuming the context window.
Surviving Compaction: Resume work after the conversation compacts without the agent forgetting which files it was editing or what task was in progress.
Large Log and Data Analysis: Have the agent script the analysis over a 45 KB access log rather than reading it into context to reason over it manually.
Multi-Platform Agent Setups: Standardize context routing across Claude Code, Cursor, and the other supported clients so behavior is consistent regardless of tool.
Cost Reduction: Cut token spend on agent-heavy workflows by removing raw tool payloads from prompts.
Team Context Analytics: Use the hosted Insight dashboard to see how much context engineering teams are saving across projects.

Monsef Holdings Pty Ltd

Freemium

A hosted knowledge base every AI agent can read and write, shared across Claude, ChatGPT, Cursor and coding agents via connectors.

Connector Setup: Add OzBrain from the connector menu in Claude or ChatGPT, sign in and approve - no code, SDK or installation required.
Nested Article Retrieval: Knowledge is broken into nested pieces so an agent loads only the slice it needs, cutting tokens, latency and hallucination.
Automatic Supersession: When newer thinking arrives, OzBrain revisits existing articles, marks the old as replaced and links forward to the current version.
Staged Writes: Changes are proposed before they land, so multiple agents can write concurrently without clobbering one another.
Change Ledger: Every edit records the agent, the article and the stated reason, giving a readable history of how the brain reached its current state.
Shared Team Brains: Point a whole team's agents at one brain so context worked out in one person's chat is immediately available in everyone else's.
Broad Client Support: Works with Claude, ChatGPT, Claude Code, Cursor, OpenClaw, Hermes Agent, Gemini Spark where available, and any connector-capable client.
Markdown Export: Export everything as plain markdown at any time, including after cancellation, with deletion meaning the content is actually removed.

Cross-Agent Continuity: Stop re-explaining the same project context when moving between Claude, ChatGPT and a coding agent.
Single Source of Truth: Replace the scatter of launch-plan copies across Drive, Downloads, email and chat with one current version agents read from.
Team Onboarding: Give a new teammate's agents the accumulated decisions, research and roadmap the rest of the team already has.
Agent-Maintained Documentation: Let agents append findings and decisions as they work, with humans reviewing and correcting in the same place.
Rules and Skills Storage: Keep coding standards, conventions and reusable skills where Claude Code and Cursor pick them up automatically.
Long-Running Research: Accumulate customer research and competitive notes across many sessions instead of losing them to chat history.