The 10 Best AI Agent Tools and Builders in 2026
"AI agent" now covers three different kinds of product. Some are ready-made agents you hand a goal to, such as Manus or Lindy. Some are builders that let operations teams connect models to business apps without code, such as Zapier AI, Gumloop and Microsoft Copilot Studio. The rest are frameworks developers use to write their own agents, such as the OpenAI Agents SDK, CrewAI, LangChain and Dify.
We picked 10 tools from the 50 agent products profiled on All About AI and ranked each for the job it does best. For every pick you get what it does, who it suits, key features, pros and cons, current pricing and a bottom line. Prices come from vendor pages as of late October 2026, and each tool links to a full profile with sources.
Most agent products bill by credits, tasks or tokens rather than flat seats. That makes cost the hardest part to predict, so we flag how each one meters usage.
10 best AI agent tools: TL;DR
- Lindy: Best AI teammate for inbox, meetings and Slack
- Manus: Best general-purpose autonomous agent
- Zapier AI: Best for connecting AI to thousands of apps
- Gumloop: Best no-code agent builder for operations teams
- Microsoft Copilot Studio: Best for Microsoft 365 organizations
- Relevance AI: Best for go-to-market agent workforces
- OpenAI Agents Platform: Best for developers building on OpenAI
- CrewAI: Best multi-agent framework for Python teams
- LangChain: Best model-agnostic open-source framework
- Dify: Best visual builder you can self-host
How we chose these tools
We ranked the tools on five criteria:
- Job fit: each pick leads a clear use, from personal assistance to enterprise automation and custom development.
- Integrations and actions: how many apps the agent can read from and act in, and whether it supports MCP and APIs.
- Control and safety: approvals before outside actions, audit logs, admin policies and deployment options.
- Pricing clarity: we noted how each product meters credits, tasks, actions or tokens.
- Openness: whether you can bring your own model keys, export code or self-host.
Comparison table
| Tool | Type | Free option | Paid from | Self-host |
|---|---|---|---|---|
| Lindy | Ready-made assistant | 7-day trial with $50 credits | $49.99/user/month | No |
| Manus | Ready-made agent | 300 daily credits | $20/month | No |
| Zapier AI | No-code automation | 100 tasks/month | $19.99/month | No |
| Gumloop | No-code builder | 5,000 credits/month | $37/month | Enterprise VPC |
| Microsoft Copilot Studio | Low-code builder | No | $0.01/credit | No |
| Relevance AI | No-code builder | No | $29/month | No |
| OpenAI Agents Platform | Developer platform | SDK free | Usage-based | SDK only |
| CrewAI | Developer framework | Open source, 50 hosted runs | Custom enterprise | Yes |
| LangChain | Developer framework | Open source | $39/seat (LangSmith) | Yes |
| Dify | Visual builder | Sandbox and Community | $590/workspace/year | Yes |
1. Lindy
What it does: Lindy is a hosted AI teammate that manages inboxes, calendars, meetings, Slack requests, CRM updates and recurring routines across connected work tools.
Best for: Professionals and Slack-based teams who want an assistant that does work rather than a builder they must configure.
Lindy launched in March 2023 as an assistant for calendars, email, travel and meeting summaries, then grew into a shared teammate. You can message it privately through email, iMessage, Slack DMs or the web app, or mention it in a Slack channel and follow the work there. It triages inboxes, drafts replies, prepares meeting briefs, records meetings, updates CRM records and runs scheduled routines such as daily briefs.
Lindy says it supports more than 1,500 integrations plus hosted MCP servers and stored API credentials. Reads happen without approval, while outside actions such as sending email can wait for approval in Slack. In 2026 the company rebuilt its memory system into separate user and team file systems refreshed every 12 hours from Slack, Gmail, meetings and tasks, according to Lindy.
Every active user can require a paid seat, monthly credits do not roll over, and Lindy is closed source with no general public API contract.
Key features
- Inbox and calendar help: triage, drafts and scheduling.
- Meeting notes: recording, summaries and answers about past calls.
- Slack teammate: shared work in channels with approvals.
- 1,500+ integrations: plus MCP servers and stored credentials.
Pros
- Useful with little setup.
- Approval controls for outside actions.
- Shared team credit pool.
Cons
- Per-active-user pricing.
- Credits expire monthly.
- Hosted and closed source.
Pricing
- Free: $50 in credits for seven days, no card required.
- Team: $49.99/user/month with 5,000 pooled credits per active user.
- Top-ups: $10 per 1,000 credits.
- Enterprise: custom, with SSO, SCIM, audit logs and HIPAA.
Bottom line
Lindy is the best choice if you want an agent that handles daily work in your inbox and Slack without building workflows. Read the full Lindy review or compare Lindy vs Manus.
2. Manus
What it does: Manus is a general-purpose agent that works in a cloud computer and returns research reports, slides, websites, code and other finished outputs.
Best for: Researchers, creators and developers who want to hand off multi-step projects from a single goal.
Manus comes from Butterfly Effect, founded in 2022 and now based in Singapore. You describe a goal and Manus plans and runs the steps itself: web research, browser actions, file work, spreadsheets, slides, websites or code. Projects group related tasks, connectors bring in outside services, and Scheduled Automations run on a timer. Manus 2.0, released September 28, 2026, adds event triggers from email, calendar, Slack or Notion, plus Manus Studio, a video editor and game development.
Manus says its new Cascade architecture picks specialized capabilities as a task needs them, and reports lower token use, faster completion and lower cost than its previous system in a company test. Manus Flex lets you plug in your own inference provider key, and an API supports tasks, follow-ups, files, webhooks and custom skills.
Credit use varies by task, unused credits do not roll over, and Manus's privacy policy permits processing user content for service improvement and research.
Key features
- Cloud computer: the agent browses, writes files and runs code.
- Automations: scheduled and event-triggered tasks.
- Manus Studio: documents, slides, websites, video and games.
- API: tasks, webhooks and custom skills.
Pros
- Handles long, open-ended tasks.
- Generous free daily credits.
- Bring-your-own model key option.
Cons
- Hard-to-predict credit use.
- Credits do not roll over.
- Content may be used to improve the service.
Pricing
- Free: 300 daily refresh credits and one concurrent task.
- Pro: $20/month for 4,000 credits, $40 for 8,000 or $200 for 40,000.
- Team: $20/seat/month per the help center, with SSO and training opt-out.
- Enterprise: custom.
Bottom line
Manus is the most capable general agent for turning a single prompt into a finished deliverable. See the full Manus review.
3. Zapier AI
What it does: Zapier AI adds model-powered steps, agentic tool use, chatbots and governance to Zapier's automation platform.
Best for: Operations teams that want AI decisions inside workflows across many business apps.
Zapier advertises more than 9,000 apps and 66,000 triggers and actions, which is the main reason to start here. An AI by Zapier step sits inside a Zap: a trigger fires, the step summarizes, classifies, extracts or writes, and the structured output flows into Gmail, Salesforce, Slack or anything else. Advanced and Premium tiers let the step call connected app actions and knowledge sources, so it behaves like an agent with guardrails.
Zapier MCP lets assistants such as Claude, ChatGPT, Cursor and Gemini call actions in your connected apps. You can use Zapier's models or connect OpenAI, Anthropic, Google Gemini, Azure OpenAI or Amazon Bedrock accounts. Admins can restrict models and tools, and per-tool approvals pause sensitive actions. Zapier reports more than 593 million AI tasks automated.
Advanced and Premium steps use three and five tasks per run, so heavy use multiplies costs.
Key features
- 9,000+ apps: triggers and actions across business software.
- AI by Zapier steps: summarize, classify, extract and act.
- Zapier MCP: let assistants call your app actions.
- Governance: model policies, PII checks, approvals and audit logs.
Pros
- Widest integration catalog.
- Model choice and bring-your-own key.
- Clear run history.
Cons
- Higher AI tiers multiply task use.
- Free plan cannot publish higher AI tiers.
- Costs harder to forecast at scale.
Pricing
- Free: 100 tasks/month.
- Professional: from $19.99/month for 750 tasks.
- Team: from $69/month for 2,000 tasks.
- Enterprise: custom, with SSO, SCIM and model opt-out.
Bottom line
Zapier AI is the safest way to put AI into workflows that touch many apps. Read the full Zapier AI review or compare Zapier AI vs Gumloop.
4. Gumloop
What it does: Gumloop is a hosted, model-agnostic builder for agents and workflows that read and write across business applications.
Best for: Nontechnical builders and operations teams automating CRM, email, research and reporting work.
Gumloop was founded in 2023 by Max Brodeur-Urbas and Rahul Behal and raised a reported $17 million Series A in January 2025. You build on a visual canvas that combines instructions, connectors and reusable skills, then run agents interactively, on a schedule, from a webhook or through the REST API. Agents work in Slack, Gmail, Salesforce, HubSpot, Notion, Linear, GitHub and Google Sheets, with more tools through MCP.
Documented use cases include lead enrichment, CRM updates, meeting briefs, support triage, monitoring and scheduled reports. Developers can add Python or JavaScript steps, and Gumloop provides its own MCP server. Model presets such as Auto, Balanced and Smartest route work across Anthropic, OpenAI, Google and other providers, and bring-your-own key can remove model-credit charges on eligible plans.
Credits vary by model, tools and compute, which makes heavy agent runs harder to budget.
Key features
- Visual canvas: agents, skills and connectors.
- Triggers: schedules, webhooks and API calls.
- MCP: connect extra tools and expose agents.
- Model routing: Auto, Balanced and Smartest presets.
Pros
- Generous free credits.
- Easy for nontechnical builders.
- Enterprise VPC deployment option.
Cons
- Variable credit costs.
- Hosted only below Enterprise.
- Model presets change over time.
Pricing
- Free: 5,000 credits/month and two concurrent runs.
- Pro: $37/month for 20,000 credits.
- Overage: $0.005 per credit.
- Enterprise: custom, with VPC deployment.
Bottom line
Gumloop is the best no-code agent builder for operations teams that want results quickly. See the full Gumloop review.
5. Microsoft Copilot Studio
What it does: Copilot Studio is Microsoft's low-code builder for agents that use Microsoft 365, Power Platform and enterprise data and publish to Teams, websites and other channels.
Best for: Organizations already standardized on Microsoft 365 and Power Platform.
Microsoft announced Copilot Studio in November 2023, folding in Power Virtual Agents. You can create generative or authored agents, connect company data with prebuilt or custom connectors, and add actions through Power Automate. Agents publish to Teams, websites, apps and external channels, and admins manage them through environments, access policies, analytics and monitoring.
Microsoft 365 Copilot licenses include building in Copilot Studio and agents in Teams, SharePoint and Copilot at no extra charge. External use is billed in Copilot Credits: Microsoft's examples count a classic answer as one credit, a generative answer as two and an agent action as five. Documentation also covers autonomous agents, computer use and voice.
Credit consumption can be hard to forecast, and you need Azure and Power Platform administration.
Key features
- Low-code designer: generative and authored agents.
- Connectors and Power Automate: act in business systems.
- Multichannel publishing: Teams, web, apps and more.
- Tenant governance: environments, policies and analytics.
Pros
- Deep Microsoft data access.
- Strong enterprise admin controls.
- Included building with Microsoft 365 Copilot.
Cons
- Credit costs vary by action.
- Requires Microsoft cloud administration.
- No self-hosting.
Pricing
- Pay-as-you-go: $0.01 per Copilot Credit through Azure.
- Capacity pack: $200/month billed annually for 25,000 credits.
- Microsoft 365 Copilot: $30/user/month, includes building.
- Pre-purchase plan: custom.
Bottom line
Copilot Studio is the natural choice for agents that live inside Microsoft 365. Read the full Microsoft Copilot Studio review.
6. Relevance AI
What it does: Relevance AI is a business agent platform for building tools, agents, knowledge bases and multi-agent workforces.
Best for: Go-to-market operators building recurring sales and marketing agents.
Relevance AI, based in San Francisco and Sydney, announced a $24 million Series B led by Bessemer in May 2025. Its platform has four parts: Tools that process inputs, Agents that hold conversations and call tools, Knowledge tables for bulk runs across datasets, and Workforce, a visual canvas for arranging several agents into one process. Invent creates a starting agent from a text description.
Agents run through chat, schedules, app triggers or API calls, and Team plans add calling and meeting agents. Relevance AI says it is model-agnostic and supports bring-your-own keys, which bypass its Vendor Credits for supported providers.
The free plan has been retired, and every tool run counts as an Action, including failed runs.
Key features
- Workforce: visual multi-agent processes.
- Invent: generate an agent from a description.
- Knowledge tables: bulk runs across data.
- Calling and meeting agents: on Team plans.
Pros
- Strong multi-agent design tools.
- Bring-your-own keys.
- API and SDK access.
Cons
- No free plan.
- Two usage meters to track.
- SSO and audit logs need Enterprise.
Pricing
- Pro: $29/month ($19 billed annually) for 2,500 Actions.
- Team: $349/month ($234 billed annually) for 7,000 Actions.
- Enterprise: custom.
Bottom line
Relevance AI is the best builder for teams designing coordinated sales and marketing agents. See the full Relevance AI review.
7. OpenAI Agents Platform
What it does: OpenAI's agent platform combines the managed Agents API, the open-source Agents SDK, the Responses API, built-in tools and ChatKit for building multi-step applications.
Best for: Developers building agents on OpenAI models with hosted tools.
OpenAI released the Responses API and Agents SDK in March 2025. With the SDK you define agents with instructions, tools, guardrails and handoffs, and a runner manages turns and tool calls. Sessions keep context, MCP connects remote tools, and human-in-the-loop steps can pause execution for review. The managed Agents API runs a Codex runtime for you, with context compaction, multi-agent orchestration and sandboxes.
Built-in tools include web search, file search, computer use, hosted shell, Code Interpreter and tracing, each with published prices. The SDK supports Python and TypeScript and can work with providers that expose compatible endpoints.
Costs span tokens, tool calls, storage and containers. OpenAI has also announced that Agent Builder and Evals will be unavailable after November 30, 2026, and recommends the SDK for workflows that should continue as code.
Key features
- Agents SDK: handoffs, guardrails, sessions and tracing.
- Agents API: managed runtime with sandboxes.
- Hosted tools: search, file search, computer use and Code Interpreter.
- MCP support: connect remote tool servers.
Pros
- Free open-source SDK.
- Strong hosted tools.
- Transparent per-tool pricing.
Cons
- Many separate usage charges.
- Tied mostly to OpenAI services.
- Agent Builder is being retired.
Pricing
- Agents SDK: free.
- Models: from $0.05 per million input tokens (gpt-5-nano).
- Web search: $10 per 1,000 calls.
- Containers: from $0.03 per 20-minute session.
Bottom line
The OpenAI Agents Platform is the most complete toolkit for developers committed to OpenAI models. Read the full OpenAI Agents Platform review.
8. CrewAI
What it does: CrewAI is an open-source Python framework for multi-agent workflows, combining autonomous Crews with controlled, event-driven Flows, plus a hosted platform.
Best for: Python teams building multi-agent systems with custom tools and model choice.
João Moura released CrewAI on GitHub in November 2023 under the MIT license. A Crew holds role-based agents, tasks, tools, memory, guardrails and structured outputs. A Flow adds event-driven starts, routers, state, retries and human input, so you can wrap an autonomous Crew in deterministic logic. CrewAI reported 1.4 billion agentic executions and 40,000 GitHub stars in its October 2025 OSS 1.0 announcement.
CrewAI connects to OpenAI, Anthropic, Google, Azure, Amazon Bedrock, LiteLLM and local models through tools such as Ollama. The hosted platform adds Crew Studio, which since July 2026 builds Flows from natural language, with more than 1,000 connectors, tracing, deployment and source-code export.
The free hosted plan allows only 50 executions a month, and multi-agent runs can raise model costs and debugging effort.
Key features
- Crews and Flows: autonomous and deterministic orchestration.
- Model choice: hosted and local models.
- Crew Studio: natural-language builder with code export.
- Tracing: built-in monitoring.
Pros
- MIT-licensed core.
- Self-host or use the cloud.
- Clean multi-agent abstractions.
Cons
- Small free hosted allowance.
- Enterprise pricing not published.
- Multi-agent runs add cost.
Pricing
- Open source: free.
- Basic hosted: $0/month with 50 executions.
- Enterprise: custom, with SSO, RBAC and private deployment.
Bottom line
CrewAI is the best framework for Python teams designing several agents that work together. See the full CrewAI review or compare CrewAI vs LangChain.
9. LangChain
What it does: LangChain is an open-source framework for building agents with provider-agnostic model integrations, tools, middleware and structured output, with LangGraph for lower-level control.
Best for: Developers who want to switch model providers freely and grow from simple agents to custom workflows.
LangChain began as Harrison Chase's side project in late 2022, and LangChain and LangGraph reached version 1.0 on October 22, 2025. The core is a simple agent loop: give it instructions, a model and tools, and it calls tools until it reaches an answer. Middleware adds hooks for human approval, summarization, PII redaction and custom behavior. When you need more control, you move into LangGraph, which supports durable state, streaming and human review.
LangChain says its frameworks have passed one billion downloads. LangSmith, its commercial platform, adds tracing, evaluation and deployment.
Model and hosting costs sit outside the framework, and older code needs migration to the langchain-classic package.
Key features
- create_agent: high-level tool-calling loop.
- Middleware: approvals, redaction and custom hooks.
- LangGraph: durable, custom agent workflows.
- LangSmith: tracing, evaluation and deployment.
Pros
- Free and open source.
- Works with many model providers.
- Clear path to advanced workflows.
Cons
- Separate model and hosting costs.
- Migration work for older apps.
- LangSmith priced separately.
Pricing
- Framework: free.
- LangSmith Developer: $0 for one seat and 5,000 traces/month.
- LangSmith Plus: $39/seat/month.
- Enterprise: custom, with self-hosted options.
Bottom line
LangChain is the best open-source foundation for developers who want control and model flexibility. Read the full LangChain review.
10. Dify
What it does: Dify is a platform for building, deploying and operating LLM apps, agent workflows and retrieval systems on a visual canvas, in the cloud or self-hosted.
Best for: Teams that want a visual builder with APIs and the option to run it on their own servers.
Dify comes from LangGenius, founded in March 2023, which says Dify runs on more than 1.4 million machines. You pick an app type such as Chatflow, Workflow or Agent, then connect prompt and model nodes, conditions, code, HTTP requests, tools and human-input steps. Knowledge bases ingest documents and power retrieval, and finished apps publish as web apps or REST APIs with streaming.
Dify is model-agnostic and supports OpenAI, Anthropic, Gemini, xAI and others through provider credentials. The Community edition is free to self-host under the Dify Open Source License, and the cloud starts with a free Sandbox.
Some commercial self-hosted uses need an Enterprise license, and self-hosting means you handle upgrades and security.
Key features
- Visual canvas: workflows, agents and human-input steps.
- Knowledge bases: document ingestion and retrieval.
- APIs: chat, workflows, files and streaming.
- Deployment choice: cloud, Community or Enterprise.
Pros
- Free self-hosting.
- Strong retrieval tools.
- Many model providers.
Cons
- License limits on some commercial self-hosting.
- Cloud message credits can run out.
- You manage self-hosted operations.
Pricing
- Sandbox cloud: free with 200 message credits/month.
- Professional: $590/workspace/year.
- Team: $1,590/workspace/year.
- Community self-hosted: free; Enterprise custom.
Bottom line
Dify is the best visual agent builder for teams that want to own their deployment. See the full Dify review.
How to choose the right AI agent tool
Start with who will build and maintain the agent:
- You want help with your own work today: Lindy for inbox, calendar and Slack, or Manus for research and deliverables.
- Operations teams without engineers: Zapier AI if you rely on many apps, Gumloop for flexible no-code agents, Relevance AI for sales and marketing workforces.
- Microsoft-based companies: Copilot Studio.
- Developers: OpenAI Agents Platform for OpenAI-native apps, CrewAI for multi-agent Python systems, LangChain for model flexibility.
- Self-hosting required: Dify, CrewAI or LangChain.
Run a pilot on one narrow, repeatable task, such as weekly reports or lead enrichment. Turn on approvals for any action that sends messages or changes records, and watch credit use for a few weeks before scaling.
FAQs
What is the best AI agent in 2026?
For personal work, Lindy and Manus are the strongest ready-made agents: Lindy for inbox, meetings and Slack, Manus for research and finished deliverables. For building your own, Zapier AI and Gumloop lead no-code options, and CrewAI and LangChain lead developer frameworks.
What is the difference between an AI agent and an automation?
A traditional automation follows fixed steps you define. An AI agent decides which steps and tools to use to reach a goal, and can adapt as it goes. Many products, such as Zapier AI and Dify, mix both: fixed workflows with AI steps that make decisions inside them.
Are there free AI agent builders?
Yes. LangChain, CrewAI and Dify's Community edition are free and open source, though you pay for models and hosting. Gumloop's free plan includes 5,000 credits a month, Zapier has a free tier, and Manus gives 300 daily credits.
Are AI agents safe to connect to business apps?
They can be with the right controls. Look for approvals before outside actions, admin policies on which tools agents may use, audit logs and SSO. Lindy, Zapier AI and Gumloop offer approval steps, and Copilot Studio and Zapier Enterprise add tenant-level governance.
How much do AI agents cost?
Most charge by usage. Lindy costs $49.99 per user per month, Manus Pro starts at $20, Zapier Professional at $19.99 and Gumloop Pro at $37. Copilot Studio bills $0.01 per credit, and developer frameworks are free apart from model and hosting costs.