| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $25/mo |
| Capabilities | 10 decomposed | 15 decomposed |
| Times Matched | 0 | 0 |
Parses markdown and MDX files from a documentation source directory and extracts semantic content blocks (headings, paragraphs, code blocks, lists) into a structured format optimized for LLM consumption. Uses AST-based parsing to preserve document hierarchy and metadata, then flattens content into a single llms.txt file with clear delimiters and context markers that help LLMs understand document structure without needing to parse raw markdown syntax.
Unique: Specifically targets the llms.txt convention (emerging standard for LLM-friendly documentation) rather than generic markdown-to-text conversion, with awareness of documentation site generators (Next.js, Astro, Docusaurus) and their directory structures
vs alternatives: Purpose-built for LLM context generation unlike generic markdown converters; understands documentation site conventions and preserves semantic hierarchy better than simple text extraction
Automatically detects and adapts to different documentation framework conventions (Next.js, Astro, Docusaurus, VitePress, Gatsby) by identifying framework-specific directory patterns, configuration files, and content organization schemes. Uses heuristic-based framework detection (checking for framework config files like next.config.js, astro.config.mjs, docusaurus.config.js) to determine the correct source directory and content structure without requiring explicit configuration.
Unique: Implements framework-agnostic detection logic that recognizes multiple documentation generators' conventions and automatically resolves content paths, eliminating the need for manual configuration across different tech stacks
vs alternatives: Eliminates configuration overhead compared to generic markdown processors that require explicit path specification; handles framework-specific quirks automatically
Walks through nested directory structures starting from a detected or configured source directory, recursively discovers all markdown and MDX files, and applies filtering rules to include/exclude content based on file patterns, directory names, and metadata. Uses file system APIs with configurable glob patterns or ignore rules to skip common non-content directories (node_modules, .git, build output) and focus only on documentation source files.
Unique: Combines recursive traversal with framework-aware filtering that understands documentation site conventions (e.g., skipping build directories, node_modules) without explicit configuration
vs alternatives: More intelligent than generic file globbing because it understands documentation project structure; faster than shell-based find commands for large trees
Transforms markdown syntax into plain text while preserving semantic meaning and document structure through strategic formatting choices. Converts markdown headers to uppercase labels with separators, converts lists to indented plain text, strips inline formatting (bold, italic) while keeping content, removes markdown-specific syntax (backticks, brackets), and preserves code blocks as indented text blocks. This approach ensures LLMs can understand content hierarchy without needing to parse markdown syntax.
Unique: Prioritizes semantic clarity for LLM consumption over markdown fidelity; uses structural formatting (uppercase headers, indentation, delimiters) instead of markdown syntax to signal document hierarchy
vs alternatives: Better for LLM context than raw markdown (which adds parsing overhead) or naive text extraction (which loses structure); optimized for the specific use case of LLM-friendly documentation
Processes MDX files containing embedded JSX components and React code by extracting text content from component props, rendering component descriptions, and handling interactive elements as plain text descriptions. Parses JSX syntax to identify component boundaries, extracts meaningful text from component children and props, and generates fallback text descriptions for components that don't have direct text equivalents (e.g., 'Interactive Code Example' for a CodeSandbox embed).
Unique: Handles MDX-specific content (React components, JSX) which generic markdown tools cannot process; extracts semantic meaning from component structures rather than treating them as unparseable syntax
vs alternatives: Enables MDX documentation to be included in llms.txt unlike markdown-only tools; better than stripping JSX entirely because it preserves component intent through fallback descriptions
Generates llms.txt output with customizable formatting options including configurable section delimiters, header formatting styles, content separators, and metadata inclusion. Allows users to specify how headers are formatted (e.g., '# HEADER' vs '=== HEADER ==='), what separators divide sections, whether to include file paths or metadata, and how to structure the final output. Supports multiple output format presets (compact, verbose, structured) to optimize for different LLM consumption patterns.
Unique: Provides format customization specifically for LLM consumption patterns rather than generic text formatting; includes preset formats optimized for different LLM architectures and use cases
vs alternatives: More flexible than fixed-format tools; allows optimization for specific LLM providers unlike one-size-fits-all markdown converters
Processes multiple markdown and MDX files in a single operation, aggregates their content into a unified llms.txt output, and maintains file-level organization through metadata or section markers. Reads all discovered files, parses each independently, concatenates converted content with clear file boundaries, and optionally includes file path information or table of contents to help LLMs navigate the aggregated content. Handles file ordering (alphabetical, by modification time, or custom) to ensure consistent output.
Unique: Designed specifically for documentation aggregation with awareness of file boundaries and logical organization; maintains context about source files unlike naive concatenation
vs alternatives: More efficient than processing files individually; preserves file-level context better than simple text concatenation
Distributes get-llms-txt as an npm package with a command-line interface that can be invoked directly or integrated into build scripts and CI/CD pipelines. Provides both programmatic API (for Node.js projects) and CLI commands (for shell scripts and automation), supports configuration via command-line arguments or config files, and integrates with npm scripts in package.json for automated llms.txt generation during builds or deployments.
Unique: Provides both CLI and programmatic API for maximum flexibility; integrates seamlessly with npm-based workflows and CI/CD systems through standard Node.js conventions
vs alternatives: More accessible than standalone tools because it leverages existing npm infrastructure; easier to integrate into existing Node.js projects than external utilities
+2 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 get-llms-txt at 30/100. get-llms-txt 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