@dhuynh95: We made Agents 3x faster (and cheaper) at web browsing by building the missing memory layer! Instead of browsing from s…
Summary
Reduck MCP introduces a memory layer for browser agents that lets them write, store and reuse navigation scripts executed on the user's logged-in Chrome, making web browsing tasks 2-3x faster and cheaper than screenshot-driven Computer Use. A curated library of official scripts for sites like LinkedIn, Google Maps, Instagram and Stripe helps solve the cold-start problem.
View Cached Full Text
Cached at: 09/30/26, 04:12 PM
We made Agents 3x faster (and cheaper) at web browsing by building the missing memory layer!
Instead of browsing from scratch or performing manual actions, Agents can now write scripts + metadata and then use it for faster future navigation 🚀 https://t.co/IoZ7eK36Rr
Reduck MCP: the memory layer to make Agents 2-3x faster for browser tasks
Reliable and fast browser use is still a challenge
2026 has been the year for coding, cyber and math agents, but broader B2B work (finance, ops, growth, etc.) and B2C automation (e-commerce, travel, etc.) haven’t been as impacted yet.
One of the key reason is simple: Agents simply do not have an easy to use APIs to integrate these systems.
Today, even if agents can use Computer Use to automate sites with no API, Amazon, Reddit, your custom ERP, Computer Use is inadequate for complex and heavy workloads because it’s:
-
Slow: every click is a loop: screenshot, think, click, screenshot again
-
Expensive: screenshots and page snapshots go into context at every step, so a task burns tokens and hits rate limits
-
**Flaky: **results vary from run to run and get worse as the context grows
Agents have no memory layer for the browser
Agents have to manually discover and navigate each time
Agents have to manually discover and navigate each time
At the heart of it, agents are slow and unreliable at Computer Use because they:
-
Waste time learning how a website works: e.g. that invoices are found by clicking “Settings” and not on “Profile”, scrolling all the way down, and clicking “Billing”.
-
Waste time redoing the action: even with a Skill that stores how to navigate, the agent still operates in a loop to click and type, check new state, think and act again, which floods its context.
Introducing Reduck MCP
Our architecture: one MCP to execute scripts as tools on your logged in Chrome through our extension
Our architecture: one MCP to execute scripts as tools on your logged in Chrome through our extension
That’s why we built Reduck MCP, the memory layer for browser actions.
Instead of browsing from scratch or performing manual actions, Agents can now write scripts + metadata on how to use it and then use it for faster future navigation.
Scripts are executed on the user’s logged in Chrome, so we have no credential / bot detection issues.
To solve the cold start problem we maintain a library of official scripts for the most used sites, such as LinkedIn, Google Maps, Instagram and Stripe.
The official scripts library on reduck.ai: search LinkedIn people, get an Instagram profile, get a YC company profile, etc.
The official scripts library on reduck.ai: search LinkedIn people, get an Instagram profile, get a YC company profile, etc.
Here is an example of script with “List Anthropic Console invoices”. It states the input it takes (none) and the output it returns (every invoice of the organization), so an agent calls it the way it calls any other tool, but also can know how to chain them.
A script states what it does, what it takes and what it returns
A script states what it does, what it takes and what it returns
If no script matches, agents can write one with Reduck MCP and use it later.
Demo
Here is Claude with Reduck MCP, against Claude with the Claude for Chrome MCP, downloading 20 invoices from 5 providers:
We run the same prompt on Opus for downloading 20 invoices from 5 vendors, one with Reduck MCP on the left, Claude with the Claude for Chrome MCP on the right
We run the same prompt on Opus for downloading 20 invoices from 5 vendors, one with Reduck MCP on the left, Claude with the Claude for Chrome MCP on the right
You can play with this example and others on Duck Voyager.
So how is Reduck 3.6x faster here?
-
**Reusable scripts for fast execution: **the catalogue has an invoice script for each of the five providers, so the agent calls run_script instead of finding its way around each billing page. This means that there is no need to do the loop with read state, think, atc, read again.
-
Parallel execution: run_script takes a batch of args, so scripts run in parallel on several tabs.
Faster on every task we ran
The invoices are one task of three. We gave Claude two more, each with the same prompt once per tool: find this week’s viral founder posts on X, and find a Reddit post from a vague memory. With Reduck MCP, Claude finished all three first, 2.5x faster on everage:
Time per task: Claude with Reduck MCP against Claude with Chrome MCP
Time per task: Claude with Reduck MCP against Claude with Chrome MCP
The time difference comes from not having to loop on the UI: with Chrome, every screenshot, click and page read is a tool call, and Claude thinks before each one. With a script, one call does the whole job on a site, so Claude made 4.2x fewer tool calls over the three tasks:
Tool calls per task: each one is a step Claude has to think about
Tool calls per task: each one is a step Claude has to think about
Create your own evals with Duck Voyager
To produce such evaluations and their 1:1 comparison, we wrote Duck Voyager, our open-source eval framework for web agents. Other examples are at voyager.reduck.ai.
It wraps the Claude Code SDK to launch agents on exactly the same prompts, except that “Use Reduck MCP” becomes “Use Claude for Chrome MCP”.
Evaluation is done with deterministic code when possible, or with custom labels from a human or an AI.
Our sample is small, so feel free to contribute your own data!
Get started in minutes
If you want to test Reduck MCP to automate complex flows on Reddit, WhatsApp, or LinkedIn, you can get started in literally minutes:
-
Create an account at reduck.ai/#signin
-
Install our Chrome extension and pair it with your account
-
Install Reduck MCP
On Claude Code CLI:
On Codex CLI:
For other MCP clients, see our Onboarding Guide.
Start a new session and get going with your first automation. You can try a prompt like:
Learn more
-
Core concepts — key concepts, such as scripts and browser execution
-
API — how to call Reduck scripts programmatically from HTTP endpoints instead of MCP calls
-
CLI — a strong alternative for parallel calls, saving script run outputs to disk locally, and piping them to other apps
-
Discord — chat with us about issues, ideas, and more
Similar Articles
@dhuynh95: Little benchmark: https://blog.reduck.ai/browser-action-memory-layer-for-faster-agents/… We make Claude Code 2.5x faste…
Reduck 推出 MCP 记忆层,通过缓存和复用浏览器操作脚本,让 AI 代理的浏览器任务速度提升 2.5 倍,并内置 LinkedIn、Google Maps、Stripe 等常用网站的官方脚本库。
@dhuynh95: Because we connect your Agent to your Chrome extension, you will be logged in, no bot detection issues. Also, we make y…
Reduck 推出 Reduck MCP,作为浏览器操作的记忆层,通过复用脚本让 AI 代理的浏览器任务提速约 2.5-3 倍,并借助 Chrome 扩展解决登录与反机器人检测问题,同时维护主流网站的官方脚本库。
@dhuynh95: Super excited to announce Reduck $3M Pre Seed round to make agents browse the web fast and reliably. As you know, Agent…
Reduck announced a $3M pre-seed round for Reduck MCP, a tool that lets AI agents learn websites once and replay deterministic browser scripts for faster, hallucination-free browsing with no token burn.
@dhuynh95: Who needs to use Amazon Agent if you can have your own Agent do it? https://reduck.ai/explore/scripts?q=Amazon… I built…
Reduck MCP provides browser scripts that enable agents to automate Amazon interactions, turning black box sites into callable tools for tasks like product searches and purchases.
@PrajwalTomar_: Most browser agents are burning your tokens on mistakes they already made. Your browser agent has ZERO memory so every …
WebCMD provides memory for browser agents like Chrome, saving site paths to avoid repeating mistakes and reducing token waste. It was tested on Reddit and ranked as the most accurate and cheapest per task in BU Bench V1.