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Last reviewed · How we check sources

AI agents · updated 1 Nov 2026

Best AI agents compared: coding, browser, business and open-source agents

A model answers. An agent acts: it plans, uses tools, checks the result and keeps going. Use the finder to shortlist 42 agents in seven categories, from coding agents and browser agents to enterprise platforms, open-source frameworks, voice and research, by your task, budget, skill, deployment and privacy needs. Every value links to the maker's own page. For the models underneath, see AI models compared.

Key takeaways

  • A model answers. An agent plans, uses tools and keeps going until the job is done.
  • 42 agents and frameworks compared, 13 of them for coding.
  • 29 offer a free plan, free use or free open-source code, per each maker's page.
  • 24 support MCP, the open standard for connecting agents to tools.

Models vs assistants vs bots vs agents

Models, assistants, bots and agents: what each one is

AnswersHelps a personReplies automaticallyPlans and acts with tools

Model
The trained AI itself. Takes text, images or audio in and produces an answer out. It does not act on its own.
Examples: Gemini 4 Argon, Claude Haiku 5.5, GPT-6.1 Terra · compare models
Assistant
An app or chat interface built on a model that helps a person, who stays in charge of each step.
Examples: ChatGPT, Claude, Gemini apps
Bot
Software that replies or acts automatically, often by fixed rules. Modern bots may use a model inside.
Examples: Support chat bots, Copilot Studio standard harness agents · learn.microsoft.com
Agent
A model plus tools and a loop: it plans, calls tools, checks results and repeats until the task is done.
Examples: Claude Code, Antigravity agent, Agents SDK agents · docs.anthropic.com

Plain-language definitions by CoolPower Index. The line between them is blurring: many products now combine an assistant with agent features.

Glossary

Model
The trained AI itself. Takes text, images or audio in and produces an answer out. It does not act on its own. Examples: Gemini 4 Argon, Claude Haiku 5.5, GPT-6.1 Terra. More
Assistant
An app or chat interface built on a model that helps a person, who stays in charge of each step. Examples: ChatGPT, Claude, Gemini apps.
Bot
Software that replies or acts automatically, often by fixed rules. Modern bots may use a model inside. Examples: Support chat bots, Copilot Studio standard harness agents. Source (opens in a new tab)
Agent
A model plus tools and a loop: it plans, calls tools, checks results and repeats until the task is done. Examples: Claude Code, Antigravity agent, Agents SDK agents. Source (opens in a new tab)
MCP (Model Context Protocol)
An open-source standard for connecting AI applications to external systems: data sources, tools and workflows. Its makers compare it to a USB-C port for AI applications. Supported by Claude, ChatGPT, Visual Studio Code, Cursor and others. Source (opens in a new tab)
A2A (Agent2Agent Protocol)
An open standard for agents to talk to other agents: discover each other, delegate tasks and share results. Originally developed by Google and donated to the Linux Foundation. MCP is agent to tool, A2A is agent to agent, and the two are designed to work together. Source (opens in a new tab)

42

agents and frameworks

26

makers

24

support MCP

29

have a free plan

Agent Finder

What should the agent do?

Shortlist: write and fix code

15 of 42 agents match. Filtered out: 27 built for other jobs.

  1. 1

    Google Antigravity

    Google · Coding · Developer

    Why: Matches your task. A free agent-first editor.

    • Enterprise controls need a paid Gemini Enterprise plan

    Free · free tier antigravity.google (opens in a new tab)

  2. 2

    Cursor

    Anysphere · Coding · Developer

    Why: Matches your task. An AI-first editor with agent and tab completion in one.

    • Plan names and bundles changed in 2026, so check the current page

    From US$8 a month · free tier · MCP cursor.com (opens in a new tab)

  3. 3

    Grok Build

    xAI · Coding · Developer

    Why: Matches your task. People who already pay for an X subscription.

    • Grok models only
    • This is Grok Build, the coding CLI. It is not the Grok app and not Grok Bot.

    From US$8 a month · MCP x.ai (opens in a new tab)

  4. 4

    OpenAI Codex

    OpenAI · Coding · Developer

    Why: Matches your task. Delegating many parallel coding tasks from ChatGPT.

    • Usage limits depend on the ChatGPT plan

    From US$8 a month · free tier · MCP · open source developers.openai.com (opens in a new tab)

  5. 5

    GitHub Copilot (agent mode and coding agent)

    GitHub (Microsoft) · Coding · Developer

    Why: Matches your task. Teams already on GitHub.

    • Cloud coding agent not on the Free plan

    From US$10 a month · free tier · MCP github.com (opens in a new tab)

How matching works

Your task, must-haves, budget, skill and deployment remove agents that do not fit. The rest get points: 3 when the agent is built for your task, 2 when it suits your skill level, 1 when it offers the autonomy you asked for and 1 for a free tier when you choose Free only. Ties are ordered by lowest published starting price, then name. Every attribute comes from the maker's own pages, linked in Details. We do not rate quality.

Compare up to 4 agents

Pick two to four agents, here or with the Compare box on a result card or table row.

All 42 agents

AgentMakerCategoryFromFree tierRuns onMCPOpen sourceCompare
AnthropicCodingFrom US$20 a month claude.com (opens in a new tab)NoYour computer, CloudYesNo
OpenAICodingFrom US$8 a month developers.openai.com (opens in a new tab)YesYour computer, CloudYesYes
GitHub (Microsoft)CodingFrom US$10 a month github.com (opens in a new tab)YesYour computer, CloudYesNo
AnysphereCodingFrom US$8 a month cursor.com (opens in a new tab)YesYour computer, CloudYesNo
CognitionCodingFrom US$20 a month devin.ai (opens in a new tab)YesYour computer, Cloud–No
ReplitCodingFrom US$20 a month replit.com (opens in a new tab)YesCloud–No
LovableCodingSee note lovable.dev (opens in a new tab)YesCloudYesNo
Amazon (AWS)CodingFrom US$20 a month kiro.dev (opens in a new tab)YesYour computer–No
GoogleCodingFree antigravity.google (opens in a new tab)YesYour computer–No
xAICodingFrom US$8 a month x.ai (opens in a new tab)NoYour computerYesNo
MetaCodingSee note dev.meta.ai (opens in a new tab)NoYour computer–No
All Hands AICodingFrom US$500 a month all-hands.dev (opens in a new tab)YesYour computer, Self-host, CloudYesYes
ClineCodingSee note cline.bot (opens in a new tab)YesYour computerYesYes
AnthropicBrowser and computer useFrom US$20 a month claude.com (opens in a new tab)NoYour computer–No
AnthropicBrowser and computer useSee note docs.anthropic.com (opens in a new tab)NoSelf-host–No
Browser UseBrowser and computer useSee note browser-use.com (opens in a new tab)YesCloud, Self-hostYesYes
Manus AIBrowser and computer useFrom US$20 a month help.manus.im (opens in a new tab)YesCloud–No
PerplexityBrowser and computer useFree perplexity.ai (opens in a new tab)YesYour computer–No
xAIAssistant with agent modeSee note x.ai (opens in a new tab)NoCloudYesNo
OpenAIAssistant with agent modeFrom US$8 a month developers.openai.com (opens in a new tab)YesCloudYesNo
AnthropicAssistant with agent modeFrom US$20 a month claude.com (opens in a new tab)YesCloud, Your computerYesNo
GoogleAssistant with agent modeFrom £4.49 a month gemini.google (opens in a new tab)YesCloud–No
MicrosoftAssistant with agent modeFrom US$30 a month microsoft.com (opens in a new tab)NoCloud–No
MicrosoftEnterprise platformFrom US$200 a month microsoft.com (opens in a new tab)NoCloudYesNo
SalesforceEnterprise platformFrom US$550 a month salesforce.com (opens in a new tab)NoCloud–No
Amazon (AWS)Enterprise platformSee note aws.amazon.com (opens in a new tab)NoCloudYesNo
GoogleEnterprise platformSee note ai.google.dev (opens in a new tab)NoCloudYesNo
AnthropicEnterprise platformSee note docs.anthropic.com (opens in a new tab)NoCloud–No
ZapierEnterprise platformFrom US$19.99 a month zapier.com (opens in a new tab)YesCloudYesNo
n8nEnterprise platformFrom €20 a month n8n.io (opens in a new tab)YesCloud, Self-hostYesYes
OpenAIFramework or SDKFree openai.com (opens in a new tab)YesSelf-hostYesYes
AnthropicFramework or SDKFree github.com (opens in a new tab)YesSelf-hostYesYes
GoogleFramework or SDKFree github.com (opens in a new tab)YesSelf-host, CloudYesYes
LangChainFramework or SDKFrom US$39 a month langchain.com (opens in a new tab)YesSelf-host, CloudYesYes
MicrosoftFramework or SDKFree github.com (opens in a new tab)YesSelf-hostYesYes
CrewAIFramework or SDKSee note crewai.com (opens in a new tab)YesSelf-host, CloudYesYes
MastraFramework or SDKFree github.com (opens in a new tab)YesSelf-host, CloudYesYes
ElevenLabsVoiceFrom US$6 a month elevenlabs.io (opens in a new tab)YesCloud–No
VapiVoiceFrom US$29 a month vapi.ai (opens in a new tab)YesCloud–No
Retell AIVoiceSee note retellai.com (opens in a new tab)YesCloud–No
GoogleResearchSee note ai.google.dev (opens in a new tab)NoCloud–No
PerplexityResearchFrom US$200 a month perplexity.ai (opens in a new tab)YesCloud–No

Prices are the lowest paid plan per person per month on the maker's page, checked 1 November 2026. A dash means not stated on the pages we checked.

At a glance, by category

    Counts from the table, not a ranking.

    Agent cost calculator

    Only published prices: model tokens from the AI models table, and Amazon Bedrock AgentCore Runtime compute. Subscription plans are in the finder and table above.

    For scale, Google says one managed agent interaction typically uses 100k to 3M tokens. ai.google.dev (opens in a new tab)

    Presets from Google's published range, counted as input tokens:

    Model tokensUS$1,500.00 developers.openai.com (opens in a new tab)

    Model tokens AgentCore compute

    Estimated monthly totalUS$1,500.00

    Your own inputs times published list prices, before caching, batch or volume discounts. Tools, storage, gateways and memory are billed separately where they apply. Products without a published price are left out.

    How models manage agents

    How an AI agent works, step by step
    1. Give it a goal and tools. You send the model a task and the tools it may use. docs.anthropic.com (opens in a new tab)
    2. The model asks for an action. It replies with a tool call, such as a click, a search or a database query, instead of a final answer. docs.anthropic.com (opens in a new tab)
    3. Your code runs the action. Your application carries out each call in an environment you control and returns the result. docs.anthropic.com (opens in a new tab)
    4. Repeat until done. The model checks the result and asks for the next step. This cycle is the agent loop. docs.anthropic.com (opens in a new tab)
    5. Guardrails and a human check. Validate inputs and outputs and keep a person in the loop for consequential steps. openai.github.io (opens in a new tab)
    How models will manage agents: tools through MCP, other agents through A2A
    PersonOrchestrator agentplans, delegates, checksSpecialist agent: researchSpecialist agent: codingSpecialist agent: financeA2ATools and dataMCPMCP toolsMCP toolsMCP tools

    Pattern described in the A2A documentation: MCP standardises how an agent reaches its tools, A2A how independent agents discover each other and delegate. Diagram by CoolPower Index.

    How to use an agent

    How to put an agent to work, step by step
    1. Name the job

      Pick one task with a clear finish line, such as reviewing a pull request or researching a topic. The finder above shortlists agents by job.

    2. Choose a product or a framework

      A product such as Claude Code works out of the box. A framework such as the OpenAI Agents SDK or Google ADK lets developers build their own. openai.github.io (opens in a new tab)

    3. Connect tools and data through MCP

      MCP is an open standard for connecting AI applications to external systems such as files, databases and tools. modelcontextprotocol.io (opens in a new tab)

    4. Run it somewhere isolated

      Hosted agents run in sandboxes. Google provisions a Linux sandbox per call, and AgentCore runs each session in its own microVM. docs.aws.amazon.com (opens in a new tab)

    5. Keep a person in the loop

      Anthropic warns that prompt injection can reach agents through web pages or images, so check consequential steps yourself. docs.anthropic.com (opens in a new tab)

    6. Watch tokens and cost

      Agents call the model many times per task. Use the calculator above with your own volumes. ai.google.dev (opens in a new tab)

    Power and compute impact

    415 TWh

    Data centre electricity use in 2024, about 1.5% of world consumption.

    Source: IEA, Energy and AI (opens in a new tab)

    ~945 TWh

    IEA projection for data centre electricity use by 2030, more than double 2024. AI is the most important driver.

    Source: IEA, Energy and AI (opens in a new tab)

    1,000 to 1,800

    Input tokens per screenshot in a computer use agent loop, so long agent runs build up tokens quickly.

    Source: Anthropic documentation (opens in a new tab)

    ~4,500

    Extra input tokens added to each request just by declaring the computer use toolset.

    Source: Anthropic documentation (opens in a new tab)

    Data centre electricity use worldwide, IEA base case

    2030 and 2035 are IEA projections (dashed). Across the IEA's cases 2035 ranges from 700 to 1700 TWh.

    Source: IEA, Energy and AI (opens in a new tab)

    Show the data as a table
    YearTWhStatus
    2024415Estimate
    2030945Projected
    20351200Projected

    Tokens behind one agent step or task, from the docs

    1,000 to 1,800

    One computer use screenshot

    Source: Anthropic docs (opens in a new tab)

    4,500

    Declaring the computer use toolset

    Source: Anthropic docs (opens in a new tab)

    75,000

    GLM-5.3 coding task, output tokens at max effort

    Source: Z.ai (opens in a new tab)

    135,000

    Antigravity agent context compaction point

    Source: Google docs (opens in a new tab)

    100,000 to 3,000,000

    One Gemini managed agent interaction, typical

    Source: Google docs (opens in a new tab)

    Different measures from different makers, shown for scale only. Each screenshot and the tool definitions are sent to the model as input tokens.

    An agent makes many model calls per task instead of one, and each call can carry screenshots, tool definitions and earlier results. That multiplies the tokens, and so the accelerator time, behind a single request. The IEA figures cover all data centres, of which AI is the main growth driver. No maker publishes energy per agent task, so we show none. For capacity and grid data see chip power, energy and market intelligence.

    Protocols that connect agents

    MCP (Model Context Protocol)

    An open-source standard for connecting AI applications to external systems: data sources, tools and workflows. Its makers compare it to a USB-C port for AI applications. Supported by Claude, ChatGPT, Visual Studio Code, Cursor and others.

    Source: modelcontextprotocol.io (opens in a new tab)

    A2A (Agent2Agent Protocol)

    An open standard for agents to talk to other agents: discover each other, delegate tasks and share results. Originally developed by Google and donated to the Linux Foundation. MCP is agent to tool, A2A is agent to agent, and the two are designed to work together.

    Source: a2a-protocol.org (opens in a new tab)

    Examples from official docs

    Show the examples

    Quoted from each maker's documentation. We did not run these and show no outputs of our own.

    A first agent with the OpenAI Agents SDK OpenAI, quoted from openai.github.io (opens in a new tab)
    from agents import Agent, Runner
    
    agent = Agent(name="Assistant", instructions="You are a helpful assistant")
    
    result = Runner.run_sync(agent, "Write a haiku about recursion in programming.")
    print(result.final_output)
    Calling Google's hosted Antigravity agent Google, quoted from ai.google.dev (opens in a new tab). Shortened from the Gemini docs.
    interaction = client.interactions.create(
        agent="antigravity-preview-09-2026",
        input="Audit https://web.dev for performance, Core Web Vitals, and SEO. ...",
        environment="remote",
    )
    Moving a Claude Code session between surfaces Anthropic, quoted from docs.anthropic.com (opens in a new tab). Commands as listed in the Claude Code overview. Teleport requires a claude.ai subscription.
    # check the install
    claude --version
    
    # pull a web or mobile session into the terminal
    claude --teleport
    
    # start a task in the cloud
    claude --cloud
    An AutoGen assistant agent Microsoft, quoted from microsoft.github.io (opens in a new tab)
    import asyncio
    from autogen_agentchat.agents import AssistantAgent
    from autogen_ext.models.openai import OpenAIChatCompletionClient
    
    async def main() -> None:
        agent = AssistantAgent("assistant", OpenAIChatCompletionClient(model="gpt-4o"))
        print(await agent.run(task="Say 'Hello World!'"))
    
    asyncio.run(main())
    A LangGraph hello world graph LangChain, quoted from docs.langchain.com (opens in a new tab)
    from langgraph.graph import StateGraph, MessagesState, START, END
    
    def mock_llm(state: MessagesState):
        return {"messages": [{"role": "ai", "content": "hello world"}]}
    
    graph = StateGraph(MessagesState)
    graph.add_node(mock_llm)
    graph.add_edge(START, "mock_llm")
    graph.add_edge("mock_llm", END)
    graph = graph.compile()
    
    graph.invoke({"messages": [{"role": "user", "content": "hi!"}]})

    Rumours and reports

    Show the reports

    Unconfirmed. Reported by named outlets, not confirmed by the companies. Each links to the report with its date.

    Confirmed since: 8 Oct 2026: Google Cloud introduced the Gemini agent, a single agent for work inside Google Workspace that Google says runs on Gemini and Anthropic Claude models. Reuters (opens in a new tab)

    Watch

    Official uploads from the organisations' own YouTube channels. Nothing loads from YouTube until you press play, then it uses youtube-nocookie.com.

    How much electricity does AI actually use? International Energy Agency on YouTube. Loads from YouTube only when you press play. Watch on YouTube
    The dots demo, take two | OpenAI DevDay 2026 OpenAI on YouTube. Loads from YouTube only when you press play. Watch on YouTube

    Next: the models behind the agents

    Prices, quality, speed and context for 109 models. Use the model finder. Latest launches are in AI news.

    Vendor-neutral. Listing an agent is not a recommendation. Checked 1 Nov 2026.

    Latest from the AI bots

    What changed this month for Grok Bot, ChatGPT Work, Gemini, Claude and Microsoft 365 Copilot, each from the maker's own page, is on AI news: AI bots and agents.

    People shaping AI agents and the platforms they run on

    6 leaders and researchers who shape the models, chips and data centres. Roles are as stated on each linked page. Photos are freely licensed and credited on each card.

    Rumours, theories and predictions

    Not fact. Everything in this section is a rumour, a theory or a forecast. Each card says where it circulates and sits beside what is actually known, with its own source. We do not endorse any of it, and none of it is investment advice.

    Rumour (0)Speculation (0)Prediction (3)

    Predictions about the race, the boom and a collapse

    Prediction Collapse

    The AI bubble bursts in 2027 or 2028

    The claim

    Joachim Klement, head of market strategy at Panmure Liberum, says his core conviction is that the AI bubble bursts in 2027 or 2028. His year-end 2027 target for the S&P 500 is 5,000 points, which he put at 36% below the level at the time.

    Circulates in: Bloomberg, via Yahoo Finance: AI Bubble Risks Worst S&P 500 Crash Since 2008, Strategist Says (opens in a new tab)

    What is known

    Prediction Collapse

    A slow leak, then defensive stocks win

    The claim

    Capital Economics forecasts the S&P 500 at 6,500 by the end of 2027, about 16% lower, if air keeps leaking out of the AI trade or the bubble bursts. It also expects a final tech-led rally in 2026 first.

    Circulates in: CNBC: Firm that correctly called the AI rally slowdown says here's where to hide out (opens in a new tab)

    What is known

    • CNBC reports that Alphabet and Meta both showed negative free cash flow in their latest quarter while spending heavily on AI infrastructure. cnbc.com (opens in a new tab)

    Prediction Collapse

    US$3.5tn of AI infrastructure written off by 2030

    The claim

    Gartner analyst Will Sommer predicts some US$3.5tn of AI infrastructure spending could be written off by the end of 2030, and that 80% of neoclouds will stop operating independently by 2030, bought or gone under.

    Circulates in: The Telegraph: The tech 'death spiral' that could destroy the AI boom (opens in a new tab)

    What is known

    • Gartner's stated reason is that enterprise and consumer AI revenue will not be enough to give profitable returns on all planned AI capital spending. Hyperscaler capex itself is filed quarterly and tracked on our investment page. telegraph.co.uk (opens in a new tab)

    Checked 1 November 2026. Rumour means an unconfirmed report of a specific event. Speculation means a theory or interpretation. Prediction means a forecast with a date or a number. See all rumours, theories and predictions Not investment advice.

    Best AI coding agents compared: free plans and prices

    13 coding agents with what each maker publishes about free use and the lowest paid plan. Listed in our usual order, not ranked.

    A dash means the maker does not publish it. Prices are list prices in US dollars, see each agent page for plan names and limits.

    Best AI agents in 2026, by type

    The 42 agents and frameworks on this page, grouped by what they do. Open any one for its sourced profile.

    Common questions

    What is an AI agent?

    An AI that can carry out tasks for you, like booking, filling in forms or writing and running code, rather than only answering questions.

    Why it matters A chat assistant tells you how to do something. An agent can go and do it, and should ask you before anything important.

    How is an agent different from a chatbot?

    A chatbot answers in a chat window. An agent can use apps, websites and files to get a job done, step by step.

    Are AI agents safe to use?

    They can make mistakes, so good agents ask for your approval before they send, buy or delete anything. Start with small, low-risk jobs.

    Do agents use a lot of computing?

    Yes. An agent may look at a screen many times to finish one job, and each look uses computing.

    Why it matters One screenshot can use around 1,000 to 1,800 input tokens, so long agent runs add up fast.

    • Around 1,000 to 1,800 tokens per screenshot

    Source: Anthropic computer use documentation

    How do I choose one?

    Use the Agent Finder: pick the job you want done and your skill level, and it shows agents that fit, each with links to the maker's own pages.

    What are the best AI coding agents?

    There is no single best one. The main coding agents are Claude Code, OpenAI Codex, GitHub Copilot, Cursor, Devin and Windsurf, Replit Agent, Kiro and Google Antigravity. The coding agents table on this page shows each one's free plan, starting price and source.

    Why it matters Pick by where you work: in a terminal, in your editor or in a browser.

    Source: Each maker's pricing page, checked 1 November 2026

    Are there free AI agents?

    Yes. GitHub Copilot, Cursor, OpenAI Codex, Google Antigravity and Perplexity Comet have free plans or free use, and frameworks such as the OpenAI Agents SDK, Claude Agent SDK, Google ADK and Mastra are free and open source. You still pay for model use where the agent calls a paid API.

    Why it matters Free plans usually have tight usage limits, so check the linked pricing page.

    Source: Each maker's pricing page or repository, checked 1 November 2026