Nango.dev has earned its reputation as a solid open-source tool for handling OAuth flows and credential management. It's a great starting point for many projects.

But here's the thing: as you move from proof-of-concept to production, especially when you're building AI agents or scalable B2B SaaS integrations, authentication is just the beginning. You'll quickly need more.

TL;DR: Nango excels at OAuth and credential management, but most production AI agents and B2B SaaS integrations need a managed "auth → actions → triggers → sync" layer with observability and compliance.

• Best Nango alternative for AI agents: Composio (agent-native SDK, actions + triggers, managed auth).

• Best for unified HRIS/ATS/accounting integrations: Merge (unified data models + managed sync).

• Best for low-code + pro-code embedded integrations: Paragon.

• Best for enterprise agent governance/security: Arcade.

• Best pro-dev workflow automation: Pipedream.

• Best open-source ETL-style option: Hotglue.

• Quick rule: Choose managed platforms to reduce TCO/compliance burden; choose open-source/self-hosted only if you can own uptime, security, and connector maintenance.

This guide compares seven Nango alternatives for developers in 2026. You'll find an evaluation framework, a detailed comparison table, and in-depth reviews covering each platform's strengths, weaknesses, and ideal use cases for AI-native applications.

How to evaluate Nango alternatives (criteria checklist)

Open-source Nango handles OAuth really well. But scaling production integrations or building AI agents? That takes more.

Here's how to evaluate your options.

Criterion 1: action and sync engine (beyond OAuth)

Authentication is step one. What happens after that matters more.

You need infrastructure to execute actions and sync data. Paid Nango tiers offer these capabilities with a code-first, self-managed approach. But when you're comparing against fully managed platforms, understanding this trade-off is critical.

An action engine executes API calls on behalf of your users. A sync engine moves data between systems.

Your checklist criterion: evaluate the sync engine & data handling

Look at how the platform moves data and executes actions. For actions: What's the latency? How does it handle errors and retries?

For data sync: Does it deliver real-time updates via webhooks or polling? Can it handle bi-directional sync, large historical backfills, and in-flight data transformations?

Criterion 2: total cost of ownership (TCO) and security

Self-hosting means your team handles uptime, scaling, security patches, and connector updates. You also need to achieve and maintain compliance certifications like SOC 2.

That "free" license can hide a lot of operational costs.

Your checklist criterion: analyze total cost of ownership (TCO) & security

Look past the licensing fee. Add up the developer hours for setup, maintenance, and troubleshooting. Factor in hosting and scaling costs.

And don't forget security audits and compliance work. A managed platform should offer SOC 2 / GDPR compliance, secure credential storage, and automatic token refreshes out-of-the-box. That alone can cut your operational costs dramatically.

Criterion 3: developer experience and agent-native tooling

AI agents need structured tools and a reliable execution framework. An LLM needs to know exactly what tools exist, what parameters they accept, and what the output looks like.

Nango's paid tiers now include a MCP (Model Context Protocol) server to expose integrations as tools. But the developer experience varies a lot between platforms.

Your checklist criterion: prioritize developer experience & agent-native SDKs

A good alternative should feel like an extension of your stack. Check the documentation quality and typed SDKs (Python, TypeScript).

For AI use cases, ask: How agent-native is this platform? Does it provide a clean framework for defining actions and triggers that an LLM can consume? Does it abstract pagination, rate limiting, and error handling into simple function calls?

Criterion 4: connector depth and extensibility

A platform's connector library often determines whether it's useful on day one. Nango's open-source connectors provide a starting point, but they mostly focus on authentication.

Production use cases need more. Specific endpoints, custom objects, complex actions.

Your checklist criterion: assess connector depth & extensibility

Don't just count logos on an integration marketplace. Look at depth.

Does the connector support all the endpoints, webhooks, and custom objects you need? And honestly, how easily can you add your own business logic or build new connectors without waiting on the vendor's roadmap?

Quick comparison of the top Nango alternatives

This table summarizes the top choices based on the criteria above.

Nango alternatives comparison (features and pricing)

In-depth reviews of the best Nango alternatives (2026)

Composio

Who Composio is best for

Developers building AI agents and LLM-powered applications who need a fast, reliable way to connect their agents to external tools and APIs. Also great for B2B SaaS companies wanting a developer-first, code-native integration platform.

Composio overview

Composio is a developer-first integration platform built for AI. It goes way beyond Nango's auth focus to provide a complete framework for tool usage: managed authentication, real-time triggers, and a powerful SDK that makes any API feel like a local function call.

With over 250 maintained integrations, Composio lets developers add capabilities to their agents, like searching Google Drive, creating Salesforce contacts, or sending Slack messages, in minutes instead of weeks.

How Composio compares to Nango

• Agent-Native SDK & Framework: Composio's agent-native SDK abstracts complex multi-step API calls into simple, typed Python/TypeScript functions. It handles the entire auth flow automatically, manages token refreshes, and provides built-in observability for every agent action. This complete "auth-to-action" layer replaces what you'd build yourself on Nango.

• Unified Actions & Triggers: Composio provides a complete execution layer, not just credential management. Define triggers ("when a new deal is created in HubSpot") and actions ("create a new folder in Google Drive") within a single framework. This enables complex, event-driven agentic workflows that react to the world and act on it.

• Fully Managed & Secure: Composio is fully managed and SOC 2 Type II compliant. No maintenance, scaling, or security overhead from self-hosting. Your engineers can focus on building the agent's core logic.

Composio limitations and trade-offs

• Newer Market Entrant: As a more recent player focused on the AI agent ecosystem, Composio's brand recognition may lag behind some legacy integration platforms.

• Agent-Centric Focus: The platform optimizes for real-time, event-driven agentic workflows. Teams looking for traditional, high-volume batch ETL pipelines might find it more tailored to action and trigger use cases.

Composio pricing

• A generous free tier is available for developers and startups.

• Pricing is transparent and usage-based, designed to scale with your application.

Merge

Who Merge is best for

B2B SaaS companies needing deep, standardized integrations within specific verticals like HRIS, ATS, Accounting, or CRM. Ideal for teams that prefer working with a unified data model over raw API access.

Merge overview

Merge is a leading Unified API platform. It abstracts away the differences between dozens of APIs in a given category (say, all HRIS systems) into a single, common data model.

This drastically simplifies development when you need to support multiple integrations in the same vertical. Think: one "payroll sync" integration that works across all your customers' providers.

How Merge compares to Nango

• Unified Data Models: Merge's standardized schema for entire API categories saves you from learning and mapping data from many different APIs. On Nango, you'd manage all that yourself.

• Managed Data Syncing: Merge provides robust, fully managed infrastructure for syncing data between third-party apps and your product. Open-source Nango doesn't include this.

• Enterprise-Ready: Merge targets enterprise use cases with strong compliance (SOC 2, ISO 27001, HIPAA), security features, and support for complex organizational needs.

Merge limitations and trade-offs

• Category-Bound: The unified model strength is also a limitation. If you need an integration outside their supported categories, you may not be able to build it on their platform.

• Abstraction Layer: The unified data model can hide endpoint-specific fields or capabilities you might want for more custom or agentic use cases.

Merge pricing

• Primarily enterprise-focused with platform fees and usage-based costs. Pricing typically starts in the mid-to-high thousands of dollars per month.

Knit

Who Knit is best for

Startups and mid-market B2B SaaS companies looking for a balance of broad integration coverage and an easy-to-use platform for customer-facing integrations.

Knit overview

Knit positions itself as a modern, developer-friendly unified API platform. It focuses on event-driven architecture and promises fast turnaround on new integration requests, which is honestly a common pain point with larger vendors.

Like Merge, Knit offers unified data models but aims for broader category coverage beyond main enterprise verticals.

How Knit compares to Nango

• Event-Driven Architecture: Knit emphasizes webhooks for real-time data updates. This delivers more efficiency and lower latency than the polling-based methods you'd typically build on Nango.

• Promise of Speed: A key part of their value proposition is building and shipping new integrations quickly, either by you using their tools or by their internal team.

• Full Integration Platform: Knit provides the full suite: authentication, data sync, and a management dashboard. All stuff you'd otherwise build, host, and maintain around Nango.

Knit limitations and trade-offs

• Depth vs. Breadth: Broad coverage across categories, but individual integration depth may not match specialized providers like Merge for certain complex verticals.

• Maturity: As a newer platform, Knit may have fewer enterprise-grade features and a smaller track record compared to established competitors.

Knit pricing

• More accessible for early-stage companies than Merge, with plans starting around $500/month.

Paragon

Who Paragon is best for

Teams wanting a dual approach: empower non-technical users with a visual workflow builder while giving developers a pro-code SDK and 'ActionKit' for complex, real-time agent integrations.

Paragon overview

Paragon offers a uniquely flexible platform that has evolved from a purely embedded iPaaS to a dual-offering solution. It keeps its popular low-code visual workflow editor but now also provides a pro-code solution ("Paragraph") and a dedicated "ActionKit" with an MCP server for real-time AI agent integrations.

How Paragon compares to Nango

• Dual Low-Code & Pro-Code: Paragon caters to both non-technical users with its visual builder and developers with a full-featured SDK and agent-specific tools. Nango's purely code-first approach doesn't offer this flexibility.

• Agent-Focused ActionKit: The ActionKit differentiates Paragon significantly for AI use cases. It provides a purpose-built framework for building and managing real-time agent actions that goes far beyond Nango's core capabilities.

• Embedded Marketplace UI: Paragon provides front-end components you can drop into your app to create a polished integration marketplace for your users.

Paragon limitations and trade-offs

• Complexity of Two Paradigms: Managing both a visual workflow builder and a pro-code SDK might create a steeper learning curve compared to platforms with a single developer experience.

• Potential for Vendor Lock-in: Logic built in the low-code visual editor ties to their platform UI, which can make migration harder compared to a purely code-based approach.

Paragon pricing

• Targets mid-market and enterprise customers, with pricing often starting at $1,000/month or more.

Arcade

Who Arcade is best for

Companies deploying production AI agents that require granular permissions, enterprise-grade governance, and a security-first architecture for tool calling.

Arcade overview

Arcade has positioned itself as an MCP (Managed Component Platform) runtime purpose-built for AI agents. It enables secure deployment, management, and governance of agent tool-calling in production.

The platform acts as a secure proxy between your agent and external APIs, enforcing permissions and providing detailed observability.

How Arcade compares to Nango

• Security-First MCP Runtime: Arcade's primary function is securing tool calls. It connects to identity providers (like Okta) to enforce granular, identity-based permissions for every single agent action. Critical for enterprise adoption, and completely outside Nango's scope.

• Enterprise Governance & Observability: Built for enterprise from the ground up. Detailed audit logs, policy enforcement, and deep observability into agent actions for compliance and security monitoring.

• Purpose-Built for Agents: Unlike general-purpose integration platforms, Arcade focuses on solving the security and governance challenges unique to deploying autonomous AI agents in a corporate environment.

Arcade limitations and trade-offs

• Specialized Focus: Arcade focuses on secure agent tool-calling and governance. It's not a general-purpose integration platform with broad data sync or ETL capabilities.

• Not an iPaaS: Teams looking for a traditional embedded iPaaS with visual builders or extensive pre-built connectors for data movement will find Arcade serves a very different, more specialized purpose.

Arcade pricing

• Enterprise-focused "Contact Sales" model. Arcade is a premium offering for teams that need to secure and govern agent deployments.

Pipedream

Who Pipedream is best for

Developers who want maximum control and like writing serverless functions to orchestrate complex workflows between APIs. Pipedream is a powerful "pro-code" option for building internal tools or backend integration logic.

Pipedream overview

Pipedream is a serverless integration platform built for developers. You connect APIs with custom code (Node.js, Python, Go) and run it as scalable, event-driven workflows.

You can use Pipedream for customer-facing integrations, but its real power is custom backend automation and connecting a massive ecosystem of tools.

How Pipedream compares to Nango

• Code-Level Control: Pipedream is all about writing code. You control every step of the workflow, data transformation, and error handling. Infinitely flexible for complex logic.

• Serverless Execution: You write the workflow logic, Pipedream handles execution, scaling, and infrastructure. No operational burden like self-hosting Nango.

• Massive Connector Library: Thousands of pre-built triggers and actions, with an active open-source community constantly contributing new components.

Pipedream limitations and trade-offs

• Not an 'Embedded' Solution: Pipedream excels at backend workflows, but it's not designed for embedded, customer-facing integration out-of-the-box. It lacks the pre-built UI and end-user management features of Paragon or Composio.

• Steep Learning Curve for Non-Devs: Its powerful, code-first nature makes it a developer favorite but inaccessible to product managers or customer success teams who might manage integrations on other platforms.

Pipedream pricing

• Generous free tier, with paid plans based on usage (invocations, compute time). Highly scalable and cost-effective for developers.

Hotglue

Who Hotglue is best for

Teams wanting an open-source, self-hostable alternative to Nango with a stronger focus on ETL (Extract, Transform, Load) and data warehousing use cases.

Hotglue overview

Hotglue is an open-source embedded iPaaS for building data integrations. You can self-host it like Nango, but Hotglue gears more towards moving and transforming large volumes of data between sources (SaaS apps) and destinations (like Snowflake, Redshift, or your own database).

How Hotglue compares to Nango

• ETL Focus: Hotglue targets data movement specifically. It includes features for data mapping and transformation using Python scripts (known as taps and targets), extending well beyond Nango's core scope of auth and actions.

• Open-Source & Self-Hosted: For teams with strict requirements for data to stay on their own infrastructure who want open-source flexibility, Hotglue offers a more complete data integration solution than Nango alone.

• Pre-built UI Components: Similar to Paragon, Hotglue offers embeddable front-end components to present integrations to your end-users.

Hotglue limitations and trade-offs

• Self-Hosting Burden: Just like Nango, the open-source version puts the burden of scaling, security, maintenance, and compliance (SOC 2) on your engineering team.

• ETL, Not Real-Time Actions: Hotglue targets primarily batch or scheduled data movement. It's not optimized for the low-latency, real-time trigger and action execution most modern AI agents need.

Hotglue pricing

• The core platform is open-source and free to self-host. Hotglue also offers a managed cloud version for teams that don't want to handle infrastructure.

How to migrate from Nango (step-by-step guide)

Migrating from a self-hosted Nango instance to a managed platform can feel daunting. But a structured approach de-risks the process and keeps things smooth for your users.

The goal: don't force users to re-authenticate, and validate the new system before full cutover.

Step 1: audit your current Nango implementation

Before writing any code, map out your existing setup. Identify all active integrations, the specific API calls you make after authentication, and any cron jobs or custom sync scripts you've built on top of Nango.

This audit becomes your migration checklist.

Step 2: plan credential migration

Nango stores refresh tokens in your own database. You need a secure, careful process for migrating these credentials to your new platform.

Most managed providers (like Composio) offer secure API endpoints or guided processes for importing existing OAuth tokens. Your users shouldn't need to reconnect their accounts.

Step 3: replicate workflows in the new platform

For each integration, map your existing sync logic to the new platform's features. A simple polling script you wrote might become a native, real-time trigger in Composio or a scheduled sync in Merge.

Focus on functional parity first. For AI agents, redefining your existing tool calls within the new platform's SDK is essential.

Step 4: execute a phased rollout

Don't switch everything at once. Migrate one or two non-critical integrations first.

Consider running new and old systems in parallel briefly to validate data consistency. Use feature flags to roll out the new integration platform to a small subset of users, monitor performance and error rates, then gradually expand until you can safely decommission the old Nango-based system.

Conclusion: choosing the right Nango alternative for AI agents

Nango solved the initial, difficult problem of API authentication really well. But the landscape has evolved. The rise of AI agents has shifted the primary challenge from simply connecting to reliably acting.

The best choice for your project depends entirely on your specific needs.

Unified APIs like Merge work great for vertical SaaS. Visual builders like Paragon serve teams with low-code requirements. But if your goal is to build powerful, reliable AI agents that interact with the digital world, a platform designed for that purpose matters.

Use the evaluation framework and comparison table in this guide to make a choice that aligns with your product roadmap and engineering resources.

To see how an agent-native framework can accelerate your build, explore Composio's free developer tier and experience how the SDK turns complex API interactions into simple function calls.

Frequently asked questions

What is the best Nango alternative for AI agents in 2026?

Composio is the best fit for AI agents. It provides managed auth plus an agent-native SDK for actions and triggers, so agents can reliably call tools in production.

Which Nango alternative is best for unified APIs (HRIS, ATS, accounting)?

Merge is best when you want a unified data model across many providers in a category (e.g., multiple HRIS systems) with managed syncing.

Do these Nango alternatives support MCP (Model Context Protocol) for agent tool calling?

Composio, Merge, Paragon, Arcade, and Pipedream support agent tooling/MCP-style workflows. Hotglue focuses more on ETL and doesn't optimize for MCP-based agent tool calling.

Is there a free or open-source alternative to Nango?

Hotglue is open-source and self-hostable. Pipedream has a free tier. Self-hosting can increase total cost of ownership because of maintenance, scaling, and security work.

How do I choose between Composio, Paragon, and Pipedream?

Choose Composio for agent-native actions/triggers. Choose Paragon if you need embedded UI plus low-code and pro-code. Choose Pipedream if you want maximum workflow flexibility with serverless code.

How long does it take to migrate off Nango?

Simple credential migration can take days. Migrating custom sync/action logic and validating production behavior often takes 2–4 weeks, depending on integration count and complexity.

Is Nango still a good choice in 2026?

Yes, for OAuth-first projects where you'll build and operate the rest of the integration stack yourself. For production agents or customer-facing integrations, managed platforms usually reduce time-to-market and long-term operational burden.

What should I look for beyond OAuth when replacing Nango?

Prioritize an action runtime, sync engine (webhooks/polling/backfills), retries/error handling, observability, and security/compliance (e.g., SOC 2, secure token storage).

Which option is best for enterprise security and governance for agents?

Arcade is best when you need granular permissions, audit logs, and governance controls for production agent tool calls.

Will switching platforms force users to re-authenticate?

Not always. Many managed providers support secure token/credential migration so users may not need to reconnect. But feasibility depends on how tokens are stored and provider policies.

Are managed integration platforms cheaper than self-hosting Nango?

Often yes, when you include engineering time, infrastructure, on-call, security patching, and compliance. Even if the open-source license is free.

What if an integration I need is missing?

Most managed platforms (like Merge) act as gatekeepers, meaning you must request new integrations. However, developer-first platforms like Composio and Pipedream allow you to build and host custom connectors or extend existing ones immediately, similar to Nango's custom config capabilities.