Chrome DevTools MCP vs Context Mode: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Chrome DevTools MCP and Context Mode — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Chrome DevTools MCP
Google Chrome DevTools
Official Chrome DevTools MCP server that lets coding agents drive, inspect and profile a live Chrome browser.
Key features
- Performance insights: Records traces with the Chrome DevTools frontend and extracts actionable findings
- Network inspection: Lets an agent read requests and responses from the live browser session
- Console access: Surfaces console messages with source-mapped stack traces for real debugging
- Screenshots: Captures the current page state on demand for the agent to reason over
- Puppeteer-backed automation: Actions automatically wait for their results rather than using fixed delays
- Standalone CLI: Ships a command-line interface for use without an MCP client
- Privacy flags: --no-performance-crux and --no-usage-statistics disable external data collection
- Broad client support: Works with Claude, Cursor, Copilot, Antigravity and other MCP-capable agents
Best for
- A coding agent reproduces a reported bug in a live page and reads the console stack trace to locate the cause
- A developer asks an agent to record a performance trace and summarise which resources block first paint
- An agent verifies a front-end change by navigating the app and confirming the network calls it expects
- A QA workflow captures screenshots across a checkout flow without writing a bespoke automation script
- An engineer debugs a source-mapped production error by having the agent inspect the deployed page directly
- A team wires the CLI into an existing pipeline to collect DevTools traces without adopting an MCP client
C
Context Mode
mksglu
An MCP server that sandboxes tool output, persists session memory in SQLite, and enforces context routing across 17 AI coding platforms.
Key features
- 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.
Best for
- 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.