ai-mldeveloper-tools

SuperAgent

superclaude-org

by superclaude-org

SuperAgent is artificial intelligence development software that orchestrates AI agents for efficient, parallel software

Orchestrates Codex and Gemini CLI agents with parallel execution across multiple working directories, enabling delegation of complex tasks to 16 specialized programming personas including backend architects, security engineers, and Python experts for simultaneous multi-project development workflows.

github stars

13

0 commentsdiscussion

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

16 specialized programming personasParallel execution across projectsWorks with multiple AI providers

best for

  • / Multi-project development workflows
  • / Complex software architecture tasks
  • / Parallel code analysis and generation
  • / Team development with specialized AI roles

capabilities

  • / Run multiple AI coding agents concurrently
  • / Execute tasks across different project directories
  • / Delegate to specialized programming personas
  • / List available specialized agents
  • / Manage parallel task execution with timeouts

what it does

Orchestrates multiple AI coding agents (Codex, Gemini, Continue) in parallel across different project directories with 16 specialized programming personas like backend architects and security engineers.

about

SuperAgent is a community-built MCP server published by superclaude-org that provides AI assistants with tools and capabilities via the Model Context Protocol. SuperAgent is artificial intelligence development software that orchestrates AI agents for efficient, parallel software It is categorized under ai ml, developer tools. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install SuperAgent 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

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

readme

SuperAgent MCP

SuperAgent is a Model Context Protocol (MCP) server that bridges MCP-compatible clients with the Codex, Gemini, and Continue CLI agents. It lets you fan out multiple CLI tasks in parallel, reuse curated system prompts, and surface results back to your client in a single, structured response.

Key Features

  • Unified agent runner: expose the Codex, Gemini, and Continue CLIs as MCP tools without additional wrappers.
  • Parallel execution: run multiple prompts concurrently with per-task timeouts and basic result formatting.
  • Agent library sync: ship ready-made system prompts that install into ~/.superagent/agents and can be extended locally.
  • Tool discovery: query the bundled list-agents tool to see which specialized agents are available at runtime.

Installation

npm install @superclaude-org/superagent

The postinstall script seeds any missing agent definition files under ~/.superagent/agents so they are immediately

Once connected, the client will discover these tools:

ToolPurposeNotable arguments
codexRun one or many Codex CLI tasks in parallel.inputs[] (prompt list), concurrency, workingDirectory, agent, extraArgs, timeoutMs
geminiRun Gemini CLI tasks with auto-approval enabled.inputs[], concurrency, workingDirectory, agent, timeoutMs
continueRun Continue CLI tasks with headless mode. Requires CONTINUE_CONFIG_PATH environment variable.inputs[], concurrency, workingDirectory, agent, timeoutMs
list-agentsList the specialized agents available to all tools.(none)

Invoking a tool

{
  "tool": "codex",
  "arguments": {
    "concurrency": 2,
    "inputs": [
      { "prompt": "Run unit tests", "workingDirectory": "/path/to/app" },
      { "prompt": "Summarize latest git changes", "agent": "technical-writer" }
    ]
  }
}

Agent Management

  • Agent definitions are Markdown files with frontmatter. You can edit or add new files in ~/.superagent/agents.
  • The list-agents tool shows each agent's name and description so you can supply the agent field when invoking codex, gemini, or continue.
  • Files shipped with the package are copied only if they do not already exist, preserving local customizations.

Continue Configuration

To use the continue tool, set the CONTINUE_CONFIG_PATH environment variable to point to your Continue config file:

export CONTINUE_CONFIG_PATH="/path/to/.continue/config.yaml"

This can be set in your MCP client configuration's env section.

Development

npm install
npm run build
npm start   # runs the compiled server
npm run dev # runs the TypeScript entrypoint with ts-node

Requires Node.js 18 or newer.

FAQ

What is the SuperAgent MCP server?
SuperAgent 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 SuperAgent?
This profile displays 71 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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MCP server reviews

Ratings

4.571 reviews
  • Yuki Wang· Dec 28, 2024

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

  • Evelyn Abbas· Dec 28, 2024

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

  • Dhruvi Jain· Dec 16, 2024

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

  • Amelia Flores· Dec 16, 2024

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

  • Amelia Rahman· Dec 16, 2024

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

  • Amelia Abbas· Dec 4, 2024

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

  • Olivia Jain· Nov 23, 2024

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

  • Aanya Khan· Nov 23, 2024

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

  • Yuki Okafor· Nov 19, 2024

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

  • Hassan Yang· Nov 19, 2024

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

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