| 1 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $25/mo |
| Capabilities | 8 decomposed | 15 decomposed |
| Times Matched | 0 | 0 |
Executes arbitrary shell commands inside Docker containers through the Model Context Protocol, translating MCP tool calls into Docker CLI invocations with container ID/name targeting. The server acts as a bridge between LLM agents and Docker's exec API, handling command serialization, stream capture, and exit code propagation back to the client.
Unique: Implements Docker command execution as a first-class MCP tool, allowing LLM agents to directly invoke container operations without requiring custom API wrappers or shell script intermediaries. Uses Docker's native exec API for in-container execution rather than SSH or container restart patterns.
vs alternatives: Simpler than building custom Docker API clients or REST wrappers because it leverages MCP's standardized tool-calling protocol, making it immediately compatible with any MCP-aware LLM without additional integration code.
Provides MCP tools to list and inspect available Docker containers (running and stopped), exposing container metadata including IDs, names, images, status, and port mappings. This enables LLM agents to discover which containers are available before targeting them for command execution, implemented via Docker API queries wrapped in MCP tool definitions.
Unique: Exposes Docker container enumeration as MCP tools rather than requiring agents to shell out to docker ps or parse CLI output, providing structured, type-safe access to container metadata within the MCP protocol.
vs alternatives: More reliable than parsing docker CLI output because it uses Docker's native API directly, and more agent-friendly than requiring custom shell commands since it returns structured data natively compatible with LLM function calling.
Provides MCP tools to control Docker container lifecycle operations (start, stop, restart, remove) by translating MCP tool calls into Docker API state-change operations. The server handles idempotency concerns (e.g., stopping an already-stopped container) and propagates operation results back to the MCP client.
Unique: Wraps Docker container state transitions as MCP tools, allowing LLM agents to orchestrate container lifecycle without needing to understand Docker CLI syntax or API details. Handles operation idempotency and error propagation transparently.
vs alternatives: More declarative and agent-friendly than shell commands because it exposes lifecycle operations as typed MCP tools, and safer than direct Docker API calls because the MCP server can enforce policies or logging before delegating to Docker.
Provides MCP tools to read, write, and inspect files within running containers by translating file operations into docker cp and docker exec commands. The server handles path resolution, permission checking, and content encoding (text vs binary) to enable agents to inspect logs, configuration files, and application state without entering the container interactively.
Unique: Abstracts container file system access through MCP tools, allowing agents to read/write files without understanding docker cp syntax or managing temporary files on the host. Handles encoding and path resolution transparently.
vs alternatives: More convenient than manual docker cp commands because it's integrated into the MCP tool interface, and safer than mounting host volumes because it operates through Docker's native file copy mechanism with built-in isolation.
Provides MCP tools to read and modify environment variables within running containers by inspecting container configuration and using docker exec to set variables dynamically. The server exposes container environment metadata and allows agents to update variables without restarting the container (for variables read at runtime) or to prepare environment changes for restart.
Unique: Exposes container environment inspection and modification as MCP tools, allowing agents to manage application configuration without understanding Docker's environment variable scoping or restart semantics. Abstracts the difference between build-time and runtime environment variables.
vs alternatives: More agent-friendly than manual docker inspect and docker exec commands because it provides structured access to environment data, and more flexible than static configuration files because it allows runtime modification without container restart.
Provides MCP tools to query Docker container resource usage statistics (CPU, memory, network I/O, block I/O) by polling the Docker stats API. The server translates real-time container metrics into structured data that agents can use for monitoring, alerting, or auto-scaling decisions.
Unique: Exposes Docker container resource metrics as MCP tools, allowing agents to make monitoring and scaling decisions without parsing docker stats CLI output or implementing custom Docker API polling. Returns structured, type-safe metric data.
vs alternatives: More agent-friendly than docker stats CLI because it returns structured JSON, and simpler than integrating Prometheus or other monitoring stacks because it provides direct access to Docker's native metrics without external infrastructure.
Provides MCP tools to retrieve container logs (stdout/stderr) by querying Docker's log driver, with support for filtering by timestamp, tail count, and follow mode. The server handles log encoding, stream buffering, and pagination to allow agents to inspect application output for debugging or log aggregation.
Unique: Wraps Docker log retrieval as MCP tools with filtering and pagination support, allowing agents to access container logs without understanding Docker's log driver architecture or managing log file paths. Handles encoding and stream buffering transparently.
vs alternatives: More convenient than docker logs CLI because it's integrated into the MCP tool interface with structured filtering, and more flexible than mounting log volumes because it works with any Docker log driver and doesn't require host-level file access.
Provides MCP tools to inspect container network configuration (IP addresses, port mappings, network connections) and test connectivity by executing network diagnostic commands (ping, curl, netstat) inside containers. The server translates network queries into docker exec invocations, allowing agents to diagnose network issues without manual container access.
Unique: Combines container network metadata inspection with in-container diagnostic command execution as MCP tools, allowing agents to diagnose network issues comprehensively without manual container access or understanding Docker's network driver architecture.
vs alternatives: More comprehensive than docker inspect alone because it includes connectivity testing, and more agent-friendly than manual docker exec commands because it provides structured results and handles common diagnostic patterns.
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 mcp-server-docker at 23/100. mcp-server-docker leads on ecosystem, while Glide is stronger on adoption and quality.
Need something different?
Search the match graph →© 2026 Unfragile. Stronger through disorder.
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