| 0 |
| 1 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $25/mo |
| Capabilities | 12 decomposed | 15 decomposed |
| Times Matched | 0 | 0 |
Exposes standardized MCP tools (create_workflow, get_workflow, update_workflow, delete_workflow, list_workflows) that translate natural language requests from Claude/ChatGPT into n8n HTTP API calls with JSON payload validation. The server implements tool handlers that parse MCP tool requests, validate workflow schema compliance, and forward authenticated requests to the n8n instance, returning structured workflow metadata (ID, name, nodes, connections, active status) back to the client.
Unique: Implements MCP tool handlers that directly map natural language requests to n8n REST API calls with full workflow graph support (nodes, connections, settings), rather than simple parameter passing. Uses stdio-based MCP protocol for bidirectional communication with Claude Desktop and ChatGPT, enabling context-aware workflow suggestions based on existing automation patterns.
vs alternatives: Unlike n8n's native UI or REST API clients, this MCP integration allows AI assistants to understand and modify entire workflow graphs conversationally while maintaining full schema compliance through n8n's validation layer.
Provides activate_workflow and deactivate_workflow MCP tools that toggle the active status of n8n workflows without modifying their definitions. These tools call n8n's state-change endpoints, returning confirmation of the new active/inactive status. The implementation handles idempotent state transitions (activating an already-active workflow returns success without error) and tracks execution history changes when workflows are toggled.
Unique: Implements idempotent state-change operations through MCP that abstract n8n's HTTP state endpoints, allowing AI assistants to safely toggle workflow status without understanding n8n's internal state machine. Integrates with MCP's tool response format to provide immediate confirmation and status feedback.
vs alternatives: Simpler and safer than direct API calls because MCP tools enforce parameter validation and return structured status confirmation, reducing the risk of invalid state transitions compared to raw REST API usage.
Reads and validates required environment variables (N8N_HOST, N8N_API_KEY) at server startup, ensuring the server can connect to n8n before accepting client requests. The implementation checks that N8N_HOST is a valid URL and N8N_API_KEY is non-empty, returning startup errors if configuration is missing or invalid. The server logs configuration status (without exposing sensitive values) for debugging.
Unique: Implements environment variable validation at server startup, ensuring configuration is correct before accepting client requests. Provides clear error messages for missing or invalid configuration, enabling quick debugging of deployment issues.
vs alternatives: Simpler than configuration files because environment variables are standard in containerized deployments; validation at startup prevents runtime errors from invalid configuration.
Provides TypeScript type definitions for all MCP tools, resources, and n8n API responses, enabling type-safe development and IDE autocompletion. The implementation includes runtime type checking for incoming MCP requests and outgoing n8n API responses, catching type mismatches before they cause runtime errors. The server exports type definitions for use by client applications and extensions.
Unique: Provides comprehensive TypeScript type definitions for all MCP tools and n8n API responses, enabling type-safe development and IDE autocompletion. Includes runtime type checking to catch type mismatches before they reach n8n API.
vs alternatives: More developer-friendly than untyped JavaScript because IDE autocompletion and compile-time error checking reduce bugs; type definitions enable external tools to build on top of the MCP server.
Exposes list_executions and get_execution MCP tools that query n8n's execution history with optional filters (workflow ID, status, date range) and pagination support. The server translates MCP tool parameters into n8n API query strings, retrieves execution records with full details (execution ID, status, start/end time, error messages, output data), and returns paginated result sets. The get_execution tool retrieves detailed execution logs including node-by-node execution traces.
Unique: Implements MCP tool handlers that translate natural language execution queries (e.g., 'show me failed executions from yesterday') into n8n API filter parameters, with automatic pagination handling. Exposes both summary lists and detailed execution traces through separate tools, allowing AI assistants to drill down from high-level status to node-level debugging information.
vs alternatives: More discoverable and safer than raw n8n API queries because MCP tools enforce parameter validation and return structured results; AI assistants can understand available filters through tool schemas without reading API documentation.
Provides delete_execution MCP tool that removes execution records from n8n's history. The tool calls n8n's execution deletion endpoint, which cascades cleanup of associated logs, output data, and temporary files. The implementation returns confirmation of deletion and validates that the execution exists before attempting removal, preventing errors from deleting non-existent records.
Unique: Implements safe deletion through MCP by validating execution existence before deletion and returning structured confirmation, reducing the risk of silent failures. Integrates with n8n's cascading cleanup to ensure no orphaned logs or temporary files remain after deletion.
vs alternatives: Safer than direct n8n API calls because MCP tool validation prevents accidental deletion of non-existent executions; structured confirmation provides audit trail for compliance.
Exposes HTTP resources (static and dynamic templates) that provide efficient context access to workflow definitions and execution details without requiring separate MCP tool calls. Static resources (/workflows, /execution-stats) return aggregated data (all workflows, execution statistics), while dynamic resource templates (/workflows/{id}, /executions/{id}) return detailed information for specific resources. The server implements resource handlers that fetch data from n8n API and format it as MCP resources, allowing clients to include workflow context directly in prompts without tool invocation overhead.
Unique: Implements MCP HTTP resources as an alternative to tool-based retrieval, allowing AI assistants to include workflow context directly in prompts without tool invocation overhead. Uses static and dynamic resource templates to provide both aggregate views (all workflows) and detailed views (specific workflow) through a unified resource interface.
vs alternatives: More efficient than repeated tool calls for context retrieval because resources are embedded in MCP messages; reduces latency and token usage compared to tool-based approaches that require separate invocations.
Implements secure authentication to n8n instances using API keys passed via N8N_API_KEY environment variable, with automatic header injection (X-N8N-API-KEY) on all HTTP requests. The server maintains a persistent connection to the n8n API endpoint (N8N_HOST) and reuses HTTP connections through Node.js's built-in connection pooling, reducing latency for repeated requests. The implementation handles authentication errors (401, 403) and returns structured error messages to MCP clients.
Unique: Implements centralized authentication through environment variables with automatic header injection on all n8n API calls, eliminating the need for per-request credential handling. Uses Node.js connection pooling to maintain persistent HTTP connections, reducing latency for rapid workflow operations.
vs alternatives: Simpler and more secure than embedding credentials in code or configuration files; connection pooling reduces latency compared to creating new connections for each request.
+4 more capabilities
Automatically inspects tabular data sources (Google Sheets, Airtable, Excel, CSV, SQL databases) to extract column names, infer field types (text, number, date, checkbox, etc.), and create bidirectional data bindings between UI components and source columns. Uses declarative component-to-column mappings that persist schema changes in real-time, enabling components to automatically reflect upstream data structure modifications without manual rebinding.
Unique: Glide's approach combines automatic schema introspection with declarative component binding, eliminating manual field mapping that competitors like Airtable require. The bidirectional sync model means changes to source column structure automatically propagate to UI components without developer intervention, reducing maintenance overhead for non-technical users.
vs alternatives: Faster to initial app than Airtable (which requires manual field configuration) and more flexible than rigid form builders because it adapts to evolving data structures automatically.
Provides 40+ pre-built, data-aware UI components (forms, tables, calendars, charts, buttons, text inputs, dropdowns, file uploads, maps, etc.) that automatically render responsively across mobile and desktop viewports. Components use a declarative binding syntax to connect to spreadsheet columns, with built-in support for computed fields, conditional visibility, and user-specific data filtering. Layout engine uses CSS Grid/Flexbox under the hood to adapt component sizing and positioning based on screen size without requiring manual breakpoint configuration.
Unique: Glide's component library is tightly integrated with data binding — components are not generic UI elements but data-aware objects that automatically sync with spreadsheet columns. This eliminates the disconnect between UI and data that exists in traditional form builders, where developers must manually wire component values to data sources.
vs alternatives: Faster to build than Bubble (which requires manual component-to-data wiring) and more mobile-optimized than Airtable's grid-centric interface, which prioritizes desktop spreadsheet metaphors over mobile-first design.
Glide scores higher at 70/100 vs n8n-workflow-builder at 35/100. n8n-workflow-builder leads on ecosystem, while Glide is stronger on adoption and quality.
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Enables multiple team members to edit apps simultaneously with role-based access control. Supports predefined roles (Owner, Editor, Viewer) with different permission levels: Owners can manage team members and publish apps, Editors can modify app design and data, Viewers can only view published apps. Team member limits vary by plan (2 free, 10 business, custom enterprise). Real-time collaboration on app design is not mentioned, suggesting changes may not be synchronized in real-time between editors.
Unique: Glide's team collaboration is built into the platform, meaning team members don't need separate accounts or complex permission configuration — they're invited via email and assigned roles directly in the app. This is more seamless than tools requiring external identity management.
vs alternatives: More integrated than Airtable (which requires separate workspace management) and simpler than GitHub-based collaboration (which requires version control knowledge), though less sophisticated than enterprise platforms with audit logging and approval workflows.
Provides pre-built app templates for common use cases (inventory management, CRM, project management, expense tracking, etc.) that users can clone and customize. Templates include sample data, pre-configured components, and example workflows, reducing time-to-first-app from hours to minutes. Templates are fully editable, allowing users to modify data sources, components, and workflows to match their specific needs. Template library is curated by Glide and updated regularly with new templates.
Unique: Glide's templates are fully functional apps with sample data and workflows, not just empty scaffolds. This allows users to immediately see how components work together and understand app structure before customizing, reducing the learning curve significantly.
vs alternatives: More complete than Airtable's templates (which are mostly empty bases) and more accessible than building from scratch, though less flexible than code-based frameworks where templates can be parameterized and generated programmatically.
Allows workflows to be triggered on a schedule (daily, weekly, monthly, or custom intervals) without manual intervention. Scheduled workflows execute at specified times and can perform batch operations (process pending records, send daily reports, sync data, etc.). Execution time is in UTC, and the exact scheduling mechanism (cron, quartz, custom) is undocumented. Failed scheduled tasks may or may not retry automatically (retry logic undocumented).
Unique: Glide's scheduled workflows are integrated with the workflow engine, meaning scheduled tasks can execute the same complex logic as event-triggered workflows (conditional logic, multi-step actions, API calls). This is more powerful than simple scheduled email tools because scheduled tasks can perform data transformations and cross-system synchronization.
vs alternatives: More integrated than Zapier's schedule trigger (which is limited to simple actions) and more accessible than cron jobs (which require server access and scripting knowledge), though less transparent about execution guarantees and failure handling than enterprise job schedulers.
Offers Glide Tables, a proprietary managed database alternative to external spreadsheets or databases, with automatic scaling and optimization for Glide apps. Glide Tables are stored in Glide's infrastructure and optimized for the data binding and query patterns used by Glide apps. Scaling limits are plan-dependent (25k-100k rows), with separate 'Big Tables' tier for larger datasets (exact scaling limits undocumented). Automatic backups and disaster recovery are mentioned but details are undocumented.
Unique: Glide Tables are optimized specifically for Glide's data binding and query patterns, meaning they're tightly integrated with the app builder and don't require separate database administration. This is more seamless than connecting external databases (which require schema design and optimization knowledge) but less flexible because data is locked into Glide's proprietary format.
vs alternatives: More managed than self-hosted databases (no administration required) and more integrated than external databases (no separate configuration), though less portable than standard databases because data cannot be easily exported or migrated.
Provides basic chart components (bar, line, pie, area charts) that visualize data from connected sources. Charts are configured visually by selecting data columns for axes, values, and grouping. Charts are responsive and adapt to mobile/tablet/desktop. Real-time updates are supported; charts refresh when underlying data changes. No custom chart types or advanced visualization options (3D, animations, etc.) are available.
Unique: Provides basic chart components with automatic real-time updates and responsive design, suitable for simple dashboards — most visual builders (Bubble, FlutterFlow) require chart plugins or custom code
vs alternatives: More integrated than Airtable's chart view because real-time updates are automatic; weaker than BI tools (Tableau, Looker) because no drill-down, filtering, or advanced visualization options
Allows users to query data using natural language (e.g., 'Show me all orders from last month with revenue > $5k') which is converted to structured database queries without SQL knowledge. Also includes AI-powered data extraction from unstructured text (emails, documents, images) to populate spreadsheet columns. Implementation details (LLM model, context window, fine-tuning approach) are undocumented, but the feature appears to use prompt-based query generation with fallback to manual query building if AI fails.
Unique: Glide's natural language query feature bridges the gap between spreadsheet users (who think in English) and database queries (which require SQL). Rather than teaching users SQL, it translates natural language to structured queries, lowering the barrier to data exploration. The data extraction capability extends this to unstructured sources, automating data entry from emails and documents.
vs alternatives: More accessible than Airtable's formula language or traditional SQL, and more integrated than bolt-on AI query tools because it's built directly into the data layer rather than as a separate search interface.
+7 more capabilities