ai-mldeveloper-tools

Glif

glifxyz

by glifxyz

Run AI workflows on Glif.app via MCP — ComfyUI image generators, meme & selfie creators, chained LLM calls and more for

Run AI workflows hosted on Glif.app via MCP, including ComfyUI-based image generators, meme generators, selfies, chained LLM calls, and more

github stars

79

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Access to Glif.app's workflow marketplaceComfyUI-based image generation

best for

  • / AI developers building creative applications
  • / Content creators needing automated image generation
  • / Developers integrating AI workflows into existing tools

capabilities

  • / Run AI workflows with custom inputs
  • / Search and discover available workflows
  • / Generate images using ComfyUI-based tools
  • / Create memes and process selfies
  • / Chain multiple LLM calls together
  • / Browse workflow details and user information

what it does

Connects to Glif.app to run AI workflows like image generators, meme creators, and chained LLM processes directly from your MCP client.

about

Glif is an official MCP server published by glifxyz that provides AI assistants with tools and capabilities via the Model Context Protocol. Run AI workflows on Glif.app via MCP — ComfyUI image generators, meme & selfie creators, chained LLM calls and more for It is categorized under ai ml, developer tools.

how to install

You can install Glif in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Glif is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

glif-mcp-server

MCP server for running AI workflows from glif.app.

For more info check out https://glif.app or join our Discord server: https://discord.gg/glif

Features

  • Run workflows with inputs
  • Get detailed information about workflows, runs, and users
  • Search and discover workflows
  • Browse and load agents

Setup

Running via npx (recommended)

If you have nodejs installed, you can run our @glifxyz/glif-mcp-server package via npx:

  1. Get your API token from https://glif.app/settings/api-tokens

  2. Add the server in your Claude Desktop config file. On macOS this is: ~/Library/Application Support/Claude/claude_desktop_config.json

    {
      "mcpServers": {
        "glif": {
          "command": "npx",
          "args": ["-y", "@glifxyz/glif-mcp-server@latest"],
          "env": {
            "GLIF_API_TOKEN": "your-token-here"
          }
        }
      }
    }
    

Running from a local checkout

git clone https://github.com/glifxyz/glif-mcp-server
cd glif-mcp-server
npm install
npm run build

Then configure your MCP client:

{
  "mcpServers": {
    "glif": {
      "command": "node",
      "args": ["/path/to/glif-mcp/build/index.js"],
      "env": {
        "GLIF_API_TOKEN": "your-token-here"
      }
    }
  }
}

You can also specify workflow IDs (comma-separated) which will be loaded automatically:

{
  "mcpServers": {
    "glif": {
      "command": "node",
      "args": ["/path/to/glif-mcp/build/index.js"],
      "env": {
        "GLIF_API_TOKEN": "your-token-here",
        "GLIF_IDS": "cm2v9aiga00008vfqdiximl2m,cm2v98jk6000r11afslqvooil"
      }
    }
  }
}

Configuration

Environment variables:

  • GLIF_API_TOKEN - Required. Your API token from https://glif.app/settings/api-tokens
  • GLIF_IDS - Optional. Comma-separated workflow IDs to load as tools automatically
  • IGNORE_DISCOVERY_TOOLS - Set to true to disable discovery tools
  • AGENT_TOOLS - Set to true to enable agent tools

Tools

Core Tools

  • run_workflow - Run a workflow with the specified ID and inputs
  • workflow_info - Get detailed information about a workflow

Discovery Tools (enabled by default)

  • list_featured_workflows - Get a curated list of featured workflows
  • search_workflows - Search for workflows by name or description
  • my_workflows - Get a list of your workflows
  • my_user_info - Get detailed information about your account

Agent Tools (disabled by default, enable with AGENT_TOOLS=true)

  • list_agents - Get a list of agents with optional filtering
  • load_agent - Load an agent and get its details including personality and workflows

Resources

  • glif://{id} - Get workflow metadata
  • glifRun://{id} - Get run details
  • glifUser://{id} - Get user profile

Development

npm install
npm run build
npm run dev     # auto-rebuild
npm run test    # run tests

Debugging

npm run inspector

Releasing

  1. Edit package.json and src/index.ts and bump the version
  2. Run npm install to update lockfile
  3. Commit and push to main
  4. Run npm run release (requires gh CLI)

License

MIT - see LICENSE

FAQ

What is the Glif MCP server?
Glif is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Glif?
This profile displays 32 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.532 reviews
  • Aarav Srinivasan· Dec 28, 2024

    I recommend Glif for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Advait Menon· Dec 20, 2024

    We evaluated Glif against two servers with overlapping tools; this profile had the clearer scope statement.

  • Ganesh Mohane· Dec 8, 2024

    Glif is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Aarav Liu· Dec 4, 2024

    Glif has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Sakshi Patil· Nov 27, 2024

    Glif is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Aarav Farah· Nov 23, 2024

    According to our notes, Glif benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Chaitanya Patil· Oct 18, 2024

    Glif has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Arjun Taylor· Oct 14, 2024

    Glif is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 25, 2024

    Glif reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Zara Haddad· Sep 21, 2024

    Strong directory entry: Glif surfaces stars and publisher context so we could sanity-check maintenance before adopting.

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