# n8n Published articles for n8n. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Send contracts for e-signature from n8n, with TurboDocx, Slack approval and SharePoint filing DevFeed: [Send contracts for e-signature from n8n, with TurboDocx, Slack approval and SharePoint filing]() Original publisher: [Read original article]() Author: n8n team Published: 2026-11-08T14:07:15Z Content type: tutorial Language: en Sources: [n8n]() Topics: [n8n](), [Slack]() Tags: [2](), [3](), [account](), [activation](), [by-partners](), [ceo](), [contracts](), [days](), [deal](), [guest-post](), [it-s](), [n8n](), [node](), [post](), [send](), [sharepoint](), [slack](), [spotlight](), [this](), [waiting](), [with]() ### AI overview The workflow takes contracts from an Excel row marked "Ready to send" through template generation, Slack approval, e-signature, and SharePoint filing. n8n schedules and coordinates the steps; TurboDocx generates a Word-template agreement as a PDF, sends it for signature, and triggers a webhook when signed. Slack approval gates sending, while Excel tracks Sent, Rejected, and Signed status. Setup requires n8n, the TurboDocx node and account, Microsoft 365 credentials, and a Slack workspace. The example supports one signer and does not handle redlines or negotiation. For self-hosted n8n, the signature webhook requires a public HTTPS callback URL. ### Source excerpt This Verified Node Spotlight is a guest post written by Nicolas Fry, CEO of TurboDocx. The deal is closed and the contract is ready. It's been sitting in someone's inbox for three days, waiting for an "OK, send it." Once it's finally ## CVE-2026-119557 - n8n from 2.14.0 through 2.46.3 Path Traversal via Databricks Node DevFeed: [CVE-2026-119557 - n8n from 2.14.0 through 2.46.3 Path Traversal via Databricks Node]() Original publisher: [Read original article]() Author: CVEFEED.io; vulncheck.com Published: 2026-10-30T12:16:42Z Content type: news Language: en Sources: [Latest High/Critical Vulnerabilitiy Feed]() Topics: [n8n](), [databricks]() Tags: [2026](), [cve](), [cve-2026-119557](), [databricks](), [n8n](), [node](), [path-traversal]() ### AI overview The excerpt reports a high-severity path traversal in n8n versions 2.14.0 through 2.46.3. Unauthenticated attackers may inject unencoded identifiers containing ../ sequences and query strings through webhook, chat, or form inputs mapped to spaceId, indexName, or filePath. The Databricks node may then reach arbitrary Databricks API endpoints using its stored credential, potentially exposing secrets. The excerpt does not provide remediation details. ### Source excerpt CVE ID :CVE-2026-119557 Published : Oct. 30, 2026, 12:16 p.m. | 1 hour, 32 minutes ago Description :n8n from 2.14.0 through 2.46.3 contains a path traversal vulnerability in the Databricks node that allows unauthenticated attackers to reach arbitrary Databricks API endpoints by injecting unencoded resource identifiers. Attackers can supply ../ sequences and query strings via webhook, chat, or form inputs mapped to spaceId, indexName, or filePath to read secrets using the stored credential. Severity: 8.2 | HIGH Visit the link for more details, such as CVSS details, affected products, timeline, and more... ## CVE-2026-119408 - n8n before 2.42.6, 2.43.3 and 3.0.1 Code Execution Outside Task Runner Isolation via Deprecated Function Nodes DevFeed: [CVE-2026-119408 - n8n before 2.42.6, 2.43.3 and 3.0.1 Code Execution Outside Task Runner Isolation via Deprecated Function Nodes]() Original publisher: [Read original article]() Author: CVEFEED.io; vulncheck.com Published: 2026-10-30T12:16:37Z Content type: news Language: en Sources: [Latest High/Critical Vulnerabilitiy Feed]() Topics: [n8n]() Tags: [2026](), [code](), [code-execution](), [cve](), [cve-2026-119408](), [deprecated](), [execution](), [function](), [hidden](), [import](), [isolation](), [javascript](), [langchain](), [n8n](), [node](), [process](), [remote](), [remote-code-execution](), [remote-code-execution-vulnerability](), [runner]() ### AI overview CVE-2026-119408 is rated High (CVSS 8.8) and affects n8n versions before 2.42.6, 2.43.x before 2.43.3, and 3.x before 3.0.1. Authenticated users able to create, modify, or import workflows can name deprecated Function, Function Item, or LangChain Code nodes to run JavaScript in the n8n main process, outside task runner isolation. ### Source excerpt CVE ID :CVE-2026-119408 Published : Oct. 30, 2026, 12:16 p.m. | 1 hour, 32 minutes ago Description :n8n before 2.42.6, 2.43.x before 2.43.3, and 3.x before 3.0.1 contains a remote code execution vulnerability via deprecated Function, Function Item, and LangChain Code nodes running outside task runner isolation. Authenticated users who can create, modify, or import workflows naming these hidden node types can execute JavaScript in the n8n main process. Severity: 8.8 | HIGH Visit the link for more details, such as CVSS details, affected products, timeline, and more... ## Why We're Moving n8n's Automation Team Beyond the Service Desk Model DevFeed: [Why We're Moving n8n's Automation Team Beyond the Service Desk Model]() Original publisher: [Read original article]() Author: Romina da Costa Published: 2026-10-29T07:10:00Z Content type: opinion Language: en Sources: [n8n]() Topics: [workflow automation](), [n8n](), [Automation]() Tags: [2](), [3](), [about](), [accelerate](), [accessible](), [agent](), [agents](), [ai](), [automation](), [build](), [desk](), [help](), [model](), [n8n](), [n8n-on-n8n](), [principles](), [service](), [service-desk](), [shares](), [team](), [uses]() ### AI overview n8n's internal automation team is shifting from clearing a centralized build backlog to helping departments build and own routine automations, while retaining complex, risky, or company-wide work. Its four principles are to train builders through coaching, reusable workflows, office hours, and departmental champions; require a baseline of current workload and results before starting a project; choose tools by fit, often buying proven SaaS instead of accepting years of internal maintenance, and use agents only when simpler workflows are inadequate; and give each automation an owner, documentation, error handling, and a handoff plan. The team is still operating as a service desk more often than intended: documentation standards are in development, and broader ownership depends on leadership support and time for teams to learn. ### Source excerpt Romina da Costa, head of internal AI and automation at n8n, shares the four principles her team uses to help every team build and own its automations. ## CVE-2026-118643 - n8n before 1.123.85, 2.43.5, and 2.44.1 Credential Exposure via Node Execution Error Data DevFeed: [CVE-2026-118643 - n8n before 1.123.85, 2.43.5, and 2.44.1 Credential Exposure via Node Execution Error Data]() Original publisher: [Read original article]() Author: CVEFEED.io; vulncheck.com Published: 2026-10-28T19:17:32Z Content type: news Language: en Sources: [Latest High/Critical Vulnerabilitiy Feed]() Topics: [n8n](), [Credential theft](), [Secrets Management]() Tags: [access-tokens](), [credential-exposure](), [cve-2026-118643](), [error](), [execution](), [git](), [google-cloud-storage](), [mongodb](), [n8n](), [node](), [passwords](), [tokens](), [users](), [vector](), [workflow]() ### AI overview When operations fail in n8n's Git, MongoDB Atlas Vector Store, or Google Cloud Storage nodes, affected versions can store credential secrets in execution error data. A user who can view workflow executions but cannot read the credential may recover Git passwords or tokens, MongoDB database passwords, or Google access tokens. The stated affected ranges are versions before 1.123.85, 2.x before 2.43.5, and 2.44.x before 2.44.1. The source rates the vulnerability 8.2 (HIGH). ### Source excerpt CVE ID :CVE-2026-118643 Published : Oct. 28, 2026, 7:17 p.m. | 2 hours ago Description :n8n before 1.123.85, 2.x before 2.43.5, and 2.44.x before 2.44.1 stores credential secrets in execution error data when operations fail in the Git, MongoDB Atlas Vector Store, and Google Cloud Storage nodes. Users who can view a workflow's executions but cannot read the credential can recover Git passwords or tokens, MongoDB database passwords, or Google access tokens from that data. Severity: 8.2 | HIGH Visit the link for more details, such as CVSS details, affected products, timeline, and more... ## CVE-2026-118645 - n8n before 1.123.85, 2.43.5, and 2.44.1 Filter Injection via Quick Base Node Where Parameter DevFeed: [CVE-2026-118645 - n8n before 1.123.85, 2.43.5, and 2.44.1 Filter Injection via Quick Base Node Where Parameter]() Original publisher: [Read original article]() Author: CVEFEED.io; vulncheck.com Published: 2026-10-28T19:17:32Z Content type: news Language: en Sources: [Latest High/Critical Vulnerabilitiy Feed]() Topics: [n8n]() Tags: [api](), [cve-2026-118645](), [filter](), [n8n](), [webhook](), [workflow]() ### AI overview CVE-2026-118645 is a filter injection flaw in n8n's Quick Base node: it sends the Where filter to the Quick Base API as raw query text. If untrusted input, such as webhook data, is used to build that filter, an attacker may cause Get Many to return every record or Delete to remove every record permitted by the workflow credential. Affected versions are n8n before 1.123.85, 2.x before 2.43.5, and 2.44.x before 2.44.1. The excerpt reports a severity score of 8.7 (High); it does not provide remediation details. ### Source excerpt CVE ID :CVE-2026-118645 Published : Oct. 28, 2026, 7:17 p.m. | 2 hours ago Description :n8n before 1.123.85, 2.x before 2.43.5, and 2.44.x before 2.44.1 contains a filter injection vulnerability in the Quick Base node, which sends the Where filter to the Quick Base API as raw query text. Attackers supplying untrusted input such as webhook data used to build the filter can make Get Many return every record or Delete remove every record with the workflow credential's privileges. Severity: 8.7 | HIGH Visit the link for more details, such as CVSS details, affected products, timeline, and more... ## Introducing n8n 3.0 DevFeed: [Introducing n8n 3.0]() Original publisher: [Read original article]() Author: Ophir Prusak Published: 2026-10-27T11:53:21Z Content type: release Language: en Sources: [n8n]() Topics: [n8n](), [Production Engineering](), [Security](), [Legacy Modernization](), [Service fabric]() Tags: [3](), [announcement](), [backup](), [beta](), [change](), [changelog](), [changes](), [cleanup](), [cloud](), [code](), [community](), [community-edition](), [container](), [credentials](), [cron](), [csv](), [data](), [n8n](), [reliability](), [security]() ### AI overview n8n 3.0 beta focuses on reliability, stability and security, with breaking changes that may require workflow or configuration updates. Changes include running manual executions on workers, removing in-memory binary storage, replacing Cron and Interval with Schedule Trigger, safer security defaults, and requiring Docker for self-hosting via npm or npx; Kubernetes and Helm deployments are unaffected. The Migration Report, available from Settings on version 2.39 or later, identifies affected workflows and settings, automates some fixes, and exports a CSV. The article recommends updating to the latest 2.x, resolving or dismissing report items, backing up, and trying a test or staging upgrade before production. Moving to 3.x cannot be rolled back except by restoring a backup. The beta is available now; stable is planned for early December. ### Source excerpt n8n 3.0 beta is out, focused on reliability, stability and security. Here's what's changing and how to get ready. ## SAP advances its autonomous enterprise push with smarter, governed Joule agents DevFeed: [SAP advances its autonomous enterprise push with smarter, governed Joule agents]() Original publisher: [Read original article]() Author: Kyt Dotson Published: 2026-10-27T08:00:21Z Content type: news Language: en Sources: [SiliconANGLE]() Topics: [agentic workflows](), [Multi Agent Systems](), [agent to agent communication](), [AI-Ready Data]() Tags: [agents](), [ai](), [ai-agents](), [ai-platform](), [artificial-intelligence](), [autonomous](), [autonomous-enterprise](), [business](), [conference](), [context](), [data](), [developers](), [enterprise](), [for-developers](), [foundation](), [foundation-models](), [intelligence](), [joule](), [joule-work](), [n8n](), [news](), [nyse-hpe](), [nyse-sap](), [reltio](), [sap](), [sap-rpt-2-0](), [sap-rpt-ts](), [ted-way](), [the-latest](), [top-story-5](), [top-story-6]() ### AI overview SAP's announcements pair more capable Joule agents with controls for enterprise use: Model Context Protocol and Agent2Agent enable context gathering and multistep workflows, while an orchestration layer provides a governed gateway for invoking agents and services. Joule Studio can also trigger n8n, whose deterministic, ordered workflows suit procedures requiring exact steps; agents can identify when to start them. SAP also describes ontology and multidomain data tools to connect business facts and unify records, plus Iceberg and Polaris support and federated queries for access without copying data. Its SAP-RPT-2.0 adds anomaly and outlier detection across tables, while SAP-RPT-TS forecasts time-indexed metrics through SAP Business Planning. The excerpt presents these as announced capabilities and intended uses, not measured results. ### Source excerpt SAP SE today announced a set of artificial intelligence innovations at its annual TechEd conference for developers, enhancing its Joule assistant solutions and Business AI Platform, including tabular data foundation models. New capabilities in Joule Work will help AI agents become more efficient and interoperate with open protocols. In this case, the Model Context Protocol [...] The post SAP advances its autonomous enterprise push with smarter, governed Joule agents appeared first on SiliconANGLE. ## AI Agent Memory: How LLM Agents Manage State in Production DevFeed: [AI Agent Memory: How LLM Agents Manage State in Production]() Original publisher: [Read original article]() Author: n8n team Published: 2026-10-23T12:20:34Z Content type: article Language: en Sources: [n8n]() Topics: [AI Context Management](), [AI Agent](), [state-management](), [AI chatbot continuity](), [Retrieval Augmented Generation (RAG)](), [Agent Harness](), [Multi Agent Systems](), [Integration testing]() Tags: [agent](), [agent-memory](), [agents](), [ai](), [ai-agent](), [ai-agent-memory](), [ai-workflows](), [architectures](), [build](), [by-partners](), [context](), [how-to](), [knowledge](), [learn](), [llm](), [llm-agents](), [manage](), [memory](), [n8n](), [production](), [state]() ### AI overview LLMs do not retain state between calls; agent memory stores information externally and retrieves relevant context for later prompts. The text distinguishes short-term session history from long-term knowledge, and contrasts RAG, which reads existing sources, with agent memory that also writes back. It outlines vector stores, files, knowledge graphs and hybrid systems, noting trade-offs in similarity, transparency, relationships and ingestion effort. It also describes consolidation, time-aware updates and deliberate forgetting as ways to manage stale or changing facts. For n8n, Simple Memory keeps a configurable chat history through the Agent's Memory port; longer-lived shared knowledge can be connected through the Tool port. Collector workflows add material to that shared layer, while acting workflows query it. The text says benchmarks provide an initial signal but recommends measuring the target workflow with memory on and off. ### Source excerpt Learn how AI agent memory works, explore short-term and long-term memory architectures, and discover how to combine n8n and Cognee to build AI workflows that retain context, share knowledge, and learn across sessions. ## Why we refreshed the n8n brand DevFeed: [Why we refreshed the n8n brand]() Original publisher: [Read original article]() Author: Jan Oberhauser Published: 2026-10-20T11:09:09Z Content type: article Language: en Sources: [n8n]() Topics: [n8n]() Tags: [agent](), [agentic](), [agentic-ai](), [agents](), [ai](), [ai-agents](), [automation](), [brand](), [color](), [community](), [community-edition](), [conference](), [control](), [data](), [ecosystem](), [events](), [flexibility](), [forum](), [logo](), [n8n](), [news]() ### AI overview n8n's refreshed identity shifts its logo from depicting connected nodes to expressing the activity and responsive systems those connections enable, reflecting the platform's growth into automation and AI agents. The typeface is intended to balance technical precision with a human feel; the pink remains, refined and supported by grays. The company says this is an evolution, not a rebuild: its builder community, Community Edition, model choice, connection, control, flexibility, and playful identity remain. The refresh launched October 14 at In The Loop, with early input from staff, leadership, and some community members; n8n invites further feedback as the identity rolls out across its product, website, community, and events. ### Source excerpt A new logo, a new typeface, and a new take on our pink, built for where n8n is going. ## Run your n8n AI workflows on NVIDIA DGX Spark, with no cloud API DevFeed: [Run your n8n AI workflows on NVIDIA DGX Spark, with no cloud API]() Original publisher: [Read original article]() Author: Jamie Madden Published: 2026-10-19T13:22:17Z Content type: tutorial Language: en Sources: [n8n]() Topics: [AI Infrastructure](), [Local AI](), [NVIDIA DGX](), [n8n](), [API](), [Ollama](), [vllm]() Tags: [ai](), [ai-workflows](), [customer-data](), [data-privacy](), [dgx-spark](), [n8n](), [nvidia](), [privacy](), [tutorial](), [workflows]() ### AI overview This tutorial explains how to serve local AI models on an NVIDIA DGX Spark and connect them to n8n workflows through a LiteLLM OpenAI-compatible endpoint. It covers model selection, memory and performance constraints, team access, and an invoice extraction workflow. The setup keeps customer data off cloud APIs, while the author notes operational limits such as slower chat during image generation and the need to check model licenses. ### Source excerpt Most small businesses want the same handful of AI jobs. They want to draft emails, summarize calls, read invoices, search their own documents, and make the odd image. Plenty of them can't send customer data to a cloud API to do it. Often the reason is data privacy ## How to Set Up n8n on the Raspberry Pi DevFeed: [How to Set Up n8n on the Raspberry Pi]() Original publisher: [Read original article]() Author: Gus Published: 2026-10-19T02:31:11Z Content type: tutorial Language: en Sources: [Pi My Life Up]() Topics: [workflow automation](), [n8n](), [Raspberry Pi](), [control-plane]() Tags: [beginner](), [docker](), [how-to](), [iot](), [n8n](), [raspberry-pi](), [servers](), [workflow](), [workflow-automation]() ### AI overview A hands-on tutorial for self-hosting n8n on a Raspberry Pi with Docker Compose. It explains installation, configuration, secure access, creating a scheduled weather workflow, and updating the deployment. ### Source excerpt Learn how to self-host n8n, a powerful workflow automation tool, on your Raspberry Pi using Docker. This tutorial covers installation, configuration with Compose files, and more. The post How to Set Up n8n on the Raspberry Pi appeared first on Pi My Life Up. ## Deploying, maintaining, and migrating production n8n on EKS DevFeed: [Deploying, maintaining, and migrating production n8n on EKS]() Original publisher: [Read original article]() Author: Husne Ozmen, Fairwinds Published: 2026-10-16T16:39:04Z Content type: article Language: en Sources: [Cloud Native Computing Foundation]() Topics: [n8n](), [Amazon Elastic Kubernetes Service](), [configuration-management]() Tags: [blog](), [eks](), [n8n](), [postgresql](), [redis](), [sqlite](), [webhook]() ### AI overview The article describes running n8n in production on Amazon EKS and migrating from a community Helm chart to n8n's official chart. It explains the queue mode architecture, storage and secrets setup, and why a full cutover was needed because the official chart's main workload and shared persistence model did not fit the existing EBS volume configuration. The team tested rollback and the migration in a non-production environment while preserving PostgreSQL, Redis, S3, IAM, and secrets. ### Source excerpt n8n is easy to try and harder to run under production traffic. A single container with SQLite works great for a quick demo. Production is a different story entirely. You need workers, webhook processors, PostgreSQL, Redis,... ## n8n Patches Multiple Security Vulnerabilities Affecting Self-Hosted Installations DevFeed: [n8n Patches Multiple Security Vulnerabilities Affecting Self-Hosted Installations]() Original publisher: [Read original article]() Author: Jeremy Published: 2026-10-14T16:13:09Z Content type: news Language: en Sources: [Noted]() Topics: [n8n](), [Security](), [Vulnerabilities](), [Self-hosted]() Tags: [cross-site-scripting](), [denial-of-service](), [n8n](), [security](), [self-hosted](), [vulnerabilities]() ### AI overview n8n's October 2026 security bulletin covers eight vulnerabilities, five classified as high severity, that primarily affect self-hosted installations. The flaws include cross-site scripting, cross-project data access, denial-of-service issues, and potential credential exposure. Patched releases are available, and cloud-hosted installations have already been updated. ### Source excerpt n8n has released security updates addressing multiple vulnerabilities affecting self-hosted installations. The flaws could expose sensitive credentials or allow unauthorized access to project data. Administrators are urged to update to the latest patched version. ## Build n8n workflows with Gemini 4 Argon: MCP, the Assistant, and Agents DevFeed: [Build n8n workflows with Gemini 4 Argon: MCP, the Assistant, and Agents]() Original publisher: [Read original article]() Author: Liam Hampton Published: 2026-10-13T16:09:03Z Content type: tutorial Language: en Sources: [n8n]() Topics: [n8n](), [agentic workflows](), [MSP MCP]() Tags: [agents](), [ai-agents](), [bring-your-own-key](), [gemini](), [gemini-4-argon](), [mcp](), [n8n](), [news]() ### AI overview The article describes three ways to use Gemini 4 Argon with n8n: connect an MCP-compatible tool to n8n's built-in MCP server to create workflows, configure the n8n Assistant with your own model provider key, or use Gemini as the model for n8n agents. It also outlines setup differences between self-hosted n8n and n8n Cloud. ### Source excerpt Gemini 4 Argon just dropped, and n8n is one of the first companies to use and integrate the model. Check out how you can use it with your existing n8n workflows and how to build new ones. Here are the benchmarks Google published: Benchmarks reported by Google. Source: Gemini 4 ## Build a morning AI news brief with You.com, Jev, and n8n DevFeed: [Build a morning AI news brief with You.com, Jev, and n8n]() Original publisher: [Read original article]() Author: n8n team Published: 2026-10-13T05:45:04Z Content type: tutorial Language: en Sources: [n8n]() Topics: [n8n](), [AI Chat](), [Slack](), [AI Infrastructure]() Tags: [article](), [n8n](), [workflow](), [you-com]() ### AI overview This tutorial explains how to build a weekday AI news brief with n8n, You.com, Jev, and Slack. It searches news, filters articles for relevance and materiality, groups coverage by story, and posts cited briefs only for topics with material news. The article estimates a typical morning costs $0.01 to $0.04. ### Source excerpt Every weekday at 8am, this workflow searches the day's AI news, scores every article for materiality at about $0.00004 apiece, and posts one cited brief per topic to Slack. Topics with no real news get no post. ## Create Scalable AI Automations with n8n DevFeed: [Create Scalable AI Automations with n8n]() Original publisher: [Read original article]() Author: Beau Carnes Published: 2026-10-09T17:04:26Z Content type: tutorial Language: en Sources: [Free Code Camp]() Topics: [n8n](), [Automation](), [AI Engineering](), [agentic workflows](), [Production Engineering](), [CI/CD]() Tags: [ai-agents](), [ai-automation](), [ai-workflows](), [automation](), [data-transformation](), [error-handling](), [human-in-the-loop](), [infrastructure](), [javascript](), [n8n](), [youtube]() ### AI overview This one-hour course teaches production-ready n8n AI automation, covering workflow architecture, APIs and data transformation, LLM-powered workflows, autonomous agents and memory, multi-agent systems, and production operations such as approvals, retries, and observability. ### Source excerpt Most automation tutorials show you how to connect two simple apps and call it a day. But building workflows that companies can actually run in production requires an entirely different skill set, one ## How n8n and Claude Code differ, and what n8n looks for in AI product managers DevFeed: [How n8n and Claude Code differ, and what n8n looks for in AI product managers]() Original publisher: [Read original article]() Author: Aakash Gupta Published: 2026-10-05T22:35:16Z Content type: article Language: en Sources: [Product Growth]() Topics: [n8n](), [AI Context Management](), [AI interaction best practices](), [Factuality scoring in AI]() Tags: [ai](), [ai-agent](), [audit](), [automation](), [builder](), [claude-code](), [n8n]() ### AI overview An interview with n8n CEO Jan Oberhauser explains how n8n supports shared, auditable business workflows while Claude Code is used for rapid prototyping. It also covers moving workflows into n8n, adding human approval and audit steps, and the technical and product skills n8n seeks in AI product managers. ### Source excerpt Do you even need n8n anymore? ## Best MCP Servers for Enterprise AI Agents in 2026 DevFeed: [Best MCP Servers for Enterprise AI Agents in 2026]() Original publisher: [Read original article]() Author: Swytchcode Team Published: 2026-10-05T16:10:00Z Content type: comparison Language: en Sources: [Swytchcode]() Topics: [Docker AI Governance](), [Loop Engineering](), [MSP MCP](), [grab agent platform]() Tags: [agent-framework](), [agents](), [ai-agents](), [api](), [apis](), [arcade](), [article](), [audit-trail](), [authentication](), [aws](), [azure](), [blast-radius](), [build](), [cloud](), [composio](), [enterprise-ai](), [mcp](), [mcp-servers](), [n8n](), [production]() ### AI overview The article compares Zapier MCP, Composio, Pipedream, Arcade, Paragon, n8n, and Swytchcode for enterprise AI agent API calls, outlining their strengths and production limits. It emphasizes identity, scoped tools, structured errors, safe retries, approvals, and audit, and describes Swytchcode as an execution layer for governed calls to internal and legacy APIs. ### Source excerpt The MCP servers enterprise teams evaluate for agent API calls in 2026: Zapier MCP, Composio, Pipedream, Arcade, Paragon, n8n, and Swytchcode, with setup screenshots, pros and cons, and production limits. ## 7 Zapier MCP Alternatives for Enterprise AI Agents in 2026 DevFeed: [7 Zapier MCP Alternatives for Enterprise AI Agents in 2026]() Original publisher: [Read original article]() Author: Swytchcode Team Published: 2026-10-05T16:00:00Z Content type: comparison Language: en Sources: [Swytchcode]() Topics: [Multi-step AI processes](), [n8n]() Tags: [2026](), [agent](), [agents](), [ai](), [ai-agent](), [ai-agents](), [alternatives](), [apis](), [arcade](), [auth](), [composio](), [enterprise](), [enterprise-ai](), [legacy](), [mcp](), [n8n](), [pricing](), [screenshots](), [setup](), [teams]() ### AI overview Zapier MCP offers a large hosted app catalog, but each successful call uses two tasks and calls can stop at the plan limit; its account model can also be awkward for products serving many customers, and legacy APIs may need custom steps. The article positions Pipedream, Composio, and Arcade as hosted catalog alternatives; n8n as a self-hosted workflow option; and Paragon and Nango as embedded integration tools for customer-specific connections. Swytchcode is presented as a separate execution layer for internal, partner, and legacy APIs: it runs on infrastructure the team owns, brokers OAuth, checks policy, supports approval gates and retries designed to avoid duplicate writes, and keeps a local audit trail. The article says the best fit depends on whether the main need is broad SaaS access, per-user authorization, self-hosting, embedded integrations, or governed production API calls. ### Source excerpt Why enterprise teams look past Zapier MCP in 2026: task-based pricing, multi-tenant auth, and legacy APIs. Composio, Pipedream, Arcade, n8n, Paragon, Nango, and Swytchcode compared with setup screenshots. ## From Home Assistant to AI agents: what Linux unlocks on the Arduino® UNO™ Q board DevFeed: [From Home Assistant to AI agents: what Linux unlocks on the Arduino® UNO™ Q board]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-10-05T10:54:24Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [UNO Q](), [Physical AI](), [Home Assistant](), [Local AI](), [streaming data analytics](), [OpenTelemetry]() Tags: [agentic-ai](), [ai-agents](), [ai-development](), [api-logging](), [arduino](), [computer-vision](), [environment](), [hardware](), [home-assistant](), [linux](), [local-nas](), [n8n](), [nas](), [pi-hole](), [real-time](), [server](), [uno-q]() ### AI overview The article presents the Arduino UNO Q as a single-board platform combining Linux applications with real-time microcontroller control. It describes running an AI coding agent, Home Assistant, n8n, Pi-hole, Frigate, and SMB storage locally, with examples of software services coordinating with sensors, actuators, and other hardware. ### Source excerpt UNO Q was designed around a dual-brain architecture that is built to bring high-performance computing and real-time hardware control together on a single board. The Linux environment on the MPU side is constructed to let developers install and run familiar open-source software - the same tools they'd reach for on a server or any popular [...] The post From Home Assistant to AI agents: what Linux unlocks on the Arduino® UNO™ Q board appeared first on Arduino Blog. ## How API Contract Testing Prevents Production Failures DevFeed: [How API Contract Testing Prevents Production Failures]() Original publisher: [Read original article]() Author: Yulia Dmitrievna Published: 2026-10-01T15:36:51Z Content type: tutorial Language: en Sources: [n8n]() Topics: [API Governance](), [CI/CD](), [API](), [Integration testing]() Tags: [ai](), [api](), [automation](), [ci-cd](), [code](), [guide](), [integrations-apis](), [n8n](), [testing](), [workflows]() ### AI overview API contract testing checks that provider and consumer interfaces still meet agreed expectations, while integration tests examine workflows and schema validation checks individual payloads. The article explains how teams can pair CI/CD contract tests with runtime response validation in n8n workflows to catch breaking API changes after deployment and alert teams before malformed data affects downstream steps. ### Source excerpt API contract testing helps you catch breaking changes before they disrupt your workflows. See how n8n validates API responses while your automations run. ## iPaaS and API Management: How They Differ and Where n8n Fits DevFeed: [iPaaS and API Management: How They Differ and Where n8n Fits]() Original publisher: [Read original article]() Author: n8n team Published: 2026-10-01T15:07:32Z Content type: comparison Language: en Sources: [n8n]() Topics: [n8n](), [API](), [API Governance](), [Product Management](), [AI Context Management]() Tags: [alternatives](), [api-management](), [compare](), [guides](), [itops](), [n8n](), [self-hosting]() ### AI overview The article compares integration platform as a service (iPaaS) with API management, explaining that they address different needs and may be used together. It presents n8n as an option for teams seeking workflow automation, API integration, self-hosting, execution control, and code extensibility. ### Source excerpt Compare iPaaS versus API management tools. See why engineering teams that need execution control, self-hosting, and code-level extensibility reach for n8n. ## You can now top up your n8n Assistant credits DevFeed: [You can now top up your n8n Assistant credits]() Original publisher: [Read original article]() Author: Ophir Prusak Published: 2026-09-30T21:35:00Z Content type: release Language: en Sources: [n8n]() Topics: [n8n](), [CI/CD]() Tags: [ai-model](), [cost](), [dashboard](), [debugging](), [llm](), [n8n]() ### AI overview n8n Cloud Starter and Pro users can buy extra Assistant credits manually or enable automatic top-ups with a monthly spending limit. Included credits are used first, extra credits carry over and expire after 12 months, and the Cloud admin dashboard tracks balances and usage. The update also describes changed monthly allowances, approximate credit ranges for typical requests, and how Assistant credits differ from Gateway credits. ### Source excerpt On n8n Cloud, you can now buy extra Assistant credits when you run out - manually or with auto top-up. Here's how it works. [Next page]()