| Quality |
| 0 |
| 1 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $25/mo |
| Capabilities | 9 decomposed | 15 decomposed |
| Times Matched | 0 | 0 |
Exposes ClickUp task management (create, read, update, delete) through the Model Context Protocol, allowing AI agents to manipulate tasks by translating MCP tool calls into authenticated ClickUp REST API requests. Implements request/response serialization for task objects including fields like status, priority, assignees, and custom fields, with error handling for API rate limits and authentication failures.
Unique: Implements MCP tool schema mapping specifically for ClickUp's nested workspace/team/space/folder/list hierarchy, translating flat MCP calls into context-aware API requests that respect ClickUp's organizational structure
vs alternatives: Provides native MCP integration for ClickUp task management where Zapier/N8N require webhook setup and polling, enabling synchronous agent-driven task operations with direct API authentication
Enables AI agents to search and retrieve ClickUp Docs (rich-text documents) through MCP tool calls, translating semantic search queries into ClickUp API document listing/retrieval endpoints. Handles document parsing, metadata extraction (created_by, updated_at, access_level), and content serialization for agent context windows.
Unique: Bridges ClickUp Docs (a rich-text document system) with MCP's tool-calling interface, allowing agents to treat internal documentation as queryable context sources without requiring separate knowledge base infrastructure
vs alternatives: Tighter integration with ClickUp's native documentation than external RAG systems, eliminating sync delays and API key management for separate knowledge bases
Allows AI agents to post messages to ClickUp task comments/chat and retrieve conversation history through MCP tool calls, translating agent outputs into ClickUp comment API requests with support for mentions, attachments, and threaded replies. Implements bidirectional synchronization of chat context between agent and ClickUp workspace.
Unique: Implements bidirectional chat synchronization through MCP, allowing agents to both consume task conversation history and contribute to it, creating a unified communication channel between AI and human teams
vs alternatives: Avoids context fragmentation by keeping agent-generated insights in ClickUp's native comment system rather than external logs, improving team visibility and reducing context switching
Dynamically generates MCP tool schemas that map ClickUp API endpoints to callable tools, handling parameter validation, type coercion, and error response formatting. Implements a registry pattern where each ClickUp API operation (task create, doc retrieve, etc.) is registered as an MCP tool with JSON Schema definitions for input validation and output typing.
Unique: Implements MCP tool registration as a first-class pattern for ClickUp API, providing structured tool discovery and validation that MCP clients (Claude, Cursor, etc.) can introspect and call with type safety
vs alternatives: Cleaner than raw REST API integration because MCP clients get native tool discovery and parameter validation, vs. agents having to manage HTTP requests and error handling manually
Runs as a standalone MCP server process that negotiates protocol versions and capabilities with multiple MCP clients (Claude Desktop, Cursor, Gemini CLI, N8N, Cline, Windsurf, Zed). Implements stdio/HTTP transport selection, client capability detection, and graceful degradation for clients with limited MCP support.
Unique: Abstracts MCP transport and client negotiation, allowing a single ClickUp MCP server to work seamlessly across Claude Desktop, Cursor, Gemini CLI, N8N, and other MCP-compatible tools without client-specific code
vs alternatives: Eliminates the need to build separate integrations for each tool (Zapier plugin, N8N node, Claude plugin) by leveraging MCP as a universal protocol
Manages ClickUp API authentication by accepting and validating API tokens, implementing secure token storage (environment variables or config files), and handling token refresh/expiration. Includes error handling for invalid tokens and automatic retry logic for transient authentication failures.
Unique: Implements ClickUp API token validation as a prerequisite for MCP tool registration, ensuring that unauthenticated servers fail fast rather than returning cryptic API errors to clients
vs alternatives: Cleaner than embedding tokens in MCP tool definitions because it centralizes authentication logic and prevents token leakage in tool schemas or logs
Resolves ClickUp workspace, team, space, folder, and list hierarchies from API responses, allowing agents to reference resources by name or ID. Implements caching of workspace metadata to reduce API calls and provides context-aware defaults for operations that require parent resource IDs.
Unique: Implements a context-aware resource resolver that maps human-readable ClickUp workspace names to API IDs, reducing the cognitive load on agents and enabling natural language task creation
vs alternatives: Avoids requiring agents to manually track ClickUp IDs by providing a semantic layer that resolves names to IDs, similar to how file systems abstract inode numbers
Standardizes ClickUp API error responses into consistent MCP error formats, implementing retry logic for transient failures (rate limits, timeouts) and providing actionable error messages for permanent failures (invalid IDs, permission denied). Includes logging and monitoring hooks for debugging agent-API interactions.
Unique: Implements MCP-aware error handling that translates ClickUp API errors into MCP error schemas, allowing clients to handle errors consistently without parsing ClickUp-specific error formats
vs alternatives: Better error transparency than raw API proxies because it classifies errors (transient vs. permanent) and provides retry logic, reducing agent confusion and improving reliability
+1 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 @taazkareem/clickup-mcp-server at 44/100. @taazkareem/clickup-mcp-server 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