n8n News

This feed includes only recent releases, roughly from the last 12 months, not the full historical archive. That is why a long-established product may have only a few news items.

6 news

n8n
AI Assistant on self-hosted simplified to a single command in 2.35

Previously, running AI Assistant self-hosted required manually enabling the instance-ai module and configuring the sandbox, model, and web search through environment variables. In 2.35, the module is enabled by default, installation takes one command, and the model provider (Anthropic, OpenAI, OpenRouter, or any OpenAI-compatible endpoint, including local ones), sandbox, and web search are configured directly in the UI.

n8n lets each instance choose its model, including a local OpenAI-compatible endpoint, without requiring the vendor's cloud; it does not provide centralized routing or quotas across multiple instances like a dedicated gateway. LLM Gateway →
n8n
A security update fixed 9 vulnerabilities, including RCE via $fromAI and sandbox escape

Nine security advisories in one release: 6 High (including an Expression Sandbox Escape via a prototype leak in $fromAI leading to Host RCE — GHSA-9x83-43r8-5hwc; RCE in the Git node; credential leaks from Strapi, SeaTable, and Mailcheck nodes; SSRF and local file reads through Gmail/Brevo) and 3 Medium (including query injection in Elasticsearch/Firestore nodes). Fixed in v1.123.73, v2.35.4 (stable), and v2.36.2 (beta); Cloud was patched automatically, while self-hosted instances require manual updates.

The vulnerability is not in Elasticsearch itself, but in the n8n connector node for it (query injection): the risk lies in the integration layer, not the search engine. Elasticsearch →
n8n
OpenTelemetry tracing for workflow and node execution

Each workflow run creates a root span with status, duration, and error, plus an optional child span for each node. Enabled with two env variables, exported to any OTLP collector (Jaeger, Tempo, Datadog, Honeycomb, Grafana Cloud) with no vendor lock-in.

Kafka currently has no native OTLP tracing on the broker side; it is usually instrumented through client libraries or Kafka Connect. n8n provides tracing out of the box with two environment variables. Apache Kafka →
n8n
Managed connection to MCP servers without manual client setup

n8n 2.22.0: the agent connects to some external MCP servers (Apify, Linear, Notion, and others from the official MCP registry) by selecting them from the node panel and logging in, without manually creating an MCP Client node and credential.

Lowers the entry barrier to the MCP protocol to selecting a connector from a list, removing the manual client+credential setup that was previously required even for standard MCP servers MCP →
n8n
SAP makes strategic investments in n8n, valuing it at $5.2 billion, with integration into Joule Studio

The company's valuation more than doubled in less than a year (from $2.5 billion). Under a commercial agreement, n8n is being natively integrated into Joule Studio, SAP Business AI Platform's agent-building environment.

MuleSoft has handled integration around SAP landscapes as an ESB for decades; the partnership embeds n8n as an alternative or complementary agent orchestration layer directly into the SAP stack MuleSoft →
n8n
The n8n MCP server can create and update workflows, not just run them

The AI client can now create and edit workflows directly in an instance through the built-in MCP server. The intermediate representation is TypeScript that passes type-checking and compilation before application, rather than raw JSON. Public preview; n8n 2.18.4+ is recommended.

Most MCP implementations give agents access to data or actions; here, the MCP server generates and validates workflow code itself—a rare example of MCP used for code generation rather than simply as an API bridge. MCP →

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