developer-tools

Alfred MCP Server

lumberjack-so

by lumberjack-so

Alfred MCP Server: create, manage & run Alfred workflow automation skills, manage MCP connections, view execution histor

Enables AI assistants to create, manage, and execute Alfred workflow automation skills, manage MCP server connections, view execution history, and handle API keys through Alfred's REST API.

github stars

0

0 commentsdiscussion

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

best for

  • / General purpose MCP workflows

capabilities

    what it does

    Enables AI assistants to create, manage, and execute Alfred workflow automation skills, manage MCP server connections, view execution history, and handle API keys through Alfred's REST API.

    about

    Alfred MCP Server is a community-built MCP server published by lumberjack-so that provides AI assistants with tools and capabilities via the Model Context Protocol. Alfred MCP Server: create, manage & run Alfred workflow automation skills, manage MCP connections, view execution histor It is categorized under developer tools.

    how to install

    You can install Alfred MCP Server 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

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

    readme

    Alfred MCP Server

    Model Context Protocol server that exposes Alfred's REST API as MCP tools for integration with Claude and other AI assistants.

    Overview

    The Alfred MCP Server provides seamless integration between Alfred's workflow automation platform and AI assistants through the Model Context Protocol. This enables AI assistants to create, manage, and execute Alfred skills, manage connections, view execution history, and handle API keys.

    Key Features

    • 20 MCP Tools covering all Alfred API endpoints
    • Dual Transport Support: HTTP (Smithery deployment) and STDIO (local Claude Desktop)
    • Type-Safe: Built with TypeScript and Zod validation
    • Fully Documented: Comprehensive tool descriptions and input schemas
    • Production Ready: Error handling, timeouts, and proper authentication

    Tools Available

    Skills Management (6 tools)

    • alfred_list_skills - List all skills with filtering, sorting, and pagination
    • alfred_get_skill - Get detailed information about a specific skill
    • alfred_create_skill - Create a new skill with steps and configuration
    • alfred_update_skill - Update an entire skill (PUT semantics)
    • alfred_patch_skill - Partially update a skill (PATCH semantics)
    • alfred_delete_skill - Delete a skill (with optional force flag)

    Connections Management (6 tools)

    • alfred_list_connections - List all MCP server connections
    • alfred_get_connection - Get connection details by ID
    • alfred_create_connection - Create a new MCP server connection
    • alfred_update_connection - Update entire connection configuration
    • alfred_patch_connection - Partially update connection settings
    • alfred_delete_connection - Remove a connection

    Execution History (5 tools)

    • alfred_list_executions - List execution history with filters
    • alfred_get_execution - Get detailed execution information
    • alfred_get_execution_trace - Get execution trace/logs for debugging
    • alfred_get_execution_stats - Get analytics and statistics
    • alfred_delete_execution - Delete an execution record

    API Key Management (3 tools)

    • alfred_create_api_key - Create a new Alfred API key
    • alfred_list_api_keys - List all API keys (without revealing full keys)
    • alfred_delete_api_key - Revoke an API key

    Installation

    Option 1: STDIO Mode (Claude Desktop)

    Add to your Claude Desktop configuration:

    ```json { "mcpServers": { "alfred": { "command": "npx", "args": ["-y", "@alfred/mcp-server"], "env": { "ALFRED_API_KEY": "alf_xxxxxxxxxxxxxxxxxxxxxxxxxxxx", "ALFRED_BASE_URL": "http://localhost:3001/api/v1" } } } } ```

    Option 2: HTTP Mode (Smithery Deployment)

    1. Visit Smithery.ai
    2. Search for "Alfred MCP Server"
    3. Configure with your API key and base URL
    4. Deploy with one click

    Configuration

    Required

    • `apiKey` - Your Alfred API key (format: `alf_xxx...`)

    Optional

    Development

    Building

    ```bash

    Install dependencies

    npm install

    Build for STDIO mode

    npm run build:stdio

    Build for HTTP deployment (Smithery)

    npm run build ```

    Project Structure

    ``` alfred-mcp/ ├── src/ │ ├── index.ts # Main server with dual transport │ ├── client.ts # Alfred API client wrapper │ ├── types.ts # TypeScript type definitions │ └── tools/ │ ├── skills.ts # Skills management tools │ ├── connections.ts # Connections management tools │ ├── executions.ts # Execution history tools │ └── auth.ts # API key management tools ├── package.json ├── tsconfig.json └── smithery.yaml # Smithery platform config ```

    License

    MIT

    FAQ

    What is the Alfred MCP Server MCP server?
    Alfred MCP Server 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 Alfred MCP Server?
    This profile displays 73 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 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.

    List & Promote Your MCP Server

    Share your MCP server with the developer community

    GET_STARTED →
    MCP server reviews

    Ratings

    4.773 reviews
    • Olivia Farah· Dec 20, 2024

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

    • Ira Gill· Dec 12, 2024

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

    • William Ghosh· Dec 8, 2024

      Alfred MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

    • Amelia Robinson· Dec 4, 2024

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

    • Ira Agarwal· Nov 27, 2024

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

    • Daniel Garcia· Nov 23, 2024

      We wired Alfred MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

    • Rahul Santra· Nov 19, 2024

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

    • Kaira Martinez· Nov 11, 2024

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

    • Harper Rao· Nov 11, 2024

      Alfred MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

    • Daniel Harris· Nov 3, 2024

      Useful MCP listing: Alfred MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.

    showing 1-10 of 73

    1 / 8