developer-tools

SuperiorAPIs

by cteaminfo

SuperiorAPIs connects AI systems with third-party APIs like Stripe and LinkedIn for seamless API to API integration and

Provides a bridge between AI systems and external APIs, enabling structured communication with third-party services through a set of callable tools built on the fastmcp framework.

github stars

0

Built on fastmcp frameworkStructured communication layer

best for

  • / AI developers building agents that need external data
  • / Integrating AI assistants with existing services
  • / Creating AI workflows that interact with APIs

capabilities

  • / Bridge AI systems to external APIs
  • / Execute structured API calls
  • / Handle third-party service communication
  • / Process API responses for AI consumption

what it does

Connects AI systems to external APIs through structured tools, enabling AI assistants to make calls to third-party services.

about

SuperiorAPIs is a community-built MCP server published by cteaminfo that provides AI assistants with tools and capabilities via the Model Context Protocol. SuperiorAPIs connects AI systems with third-party APIs like Stripe and LinkedIn for seamless API to API integration and It is categorized under developer tools.

how to install

You can install SuperiorAPIs 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

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

readme

MCP SuperiorAPIs Local

This project is a Python-based MCP Server that dynamically retrieves plugin definitions from SuperiorAPIs and auto-generates MCP tool functions based on their OpenAPI schemas.

It operates in stdio mode, making it ideal for local development and testing with AI clients.

If you need to integrate using HTTP or SSE protocols, please refer to: CTeaminfo/mcp_superiorapis_remote

📂 Project Structure

mcp_superiorapis_local/
├── src/mcp_superiorapis_local/     # Main program
│   ├── __init__.py           # Package initialization
│   └── server.py             # MCP server implementation
├── tests/                    # Test files
├── pyproject.toml            # Project config & dependencies
├── uv.lock                   # Locked dependencies
└── README.md                 # Project documentation (this file)

🚀 Quick Start

1. Environment Preparation

Prerequisites:

2. Clone the Project

# Using HTTPS
git clone https://github.com/CTeaminfo/mcp_superiorapis_local.git

# Using SSH
git clone git@github.com:CTeaminfo/mcp_superiorapis_local.git
cd mcp_superiorapis_local

3. Install uv (if not installed)

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# Or use pip
pip install uv

4. Install Dependencies

# Create virtual environment
uv venv --python 3.13

# Install dependencies
uv sync

# Or use pip
pip install -e .

5. Configure Environment Variables

# Set your Superior APIs token
export TOKEN=your_superior_apis_token_here

# Windows CMD
set TOKEN=your_superior_apis_token_here

Token Authentication Instructions:

  • Get your token from Superior APIs
  • Set the TOKEN environment variable before running the server

6. Start the Server


python -m mcp_superiorapis_local

or

python src/mcp_superiorapis_local/server.py

7. Verify Deployment

The server will:

  1. Fetch plugin data from SuperiorAPIs
  2. Dynamically generate MCP tool functions
  3. Register the tools
  4. Start the MCP server in stdio mode

🔌 MCP Client Integration

With uvx on Pip

Configure MCP server with uvx on pip(No need to download source code):

{
  "mcpServers": {
    "mcp_superiorapis_local": {
      "command": "uvx",
      "args": [
        "mcp-superiorapis" // https://pypi.org/project/mcp-superiorapis/
      ],
      "env": {
        "TOKEN": "your_superior_apis_token_here"
      }
    }
  }
}

Local Mode

{
  "mcp_superiorapis_local": {
    "command": "uv",
    "args": [
      "run",
      "--directory",
      "/path/to/mcp_superiorapis_local",
      "python",
      "-m",
      "mcp_superiorapis_local"
    ],
    "env": {
      "TOKEN": "your_superior_apis_token_here"
    }
  }
}

🔧 Startup Steps

# 1. Navigate to the project directory
cd mcp_superiorapis_local

# 2. Activate the virtual environment
.venv\Scripts\activate

# 3. Set environment variable
set TOKEN=your_superior_apis_token_here

# 4. Run the project
python -m mcp_superiorapis_local

or

python src/mcp_superiorapis_local/server.py

Note:

  • Dependencies only need to be installed once (using pip install -e . or uv sync)
  • After a reboot, you only need to activate the virtual environment and set the environment variable
  • Once the virtual environment is active, the command prompt will show a (venv) prefix

🔗 Related Links

MCPHub Certification

This project is officially certified by MCPHub.

View this project on MCPHub: 🔗 https://mcphub.com/mcp-servers/CTeaminfo/mcp-superiorapis

FAQ

What is the SuperiorAPIs MCP server?
SuperiorAPIs 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 SuperiorAPIs?
This profile displays 10 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.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

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

  • Piyush G· Sep 9, 2024

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

  • Chaitanya Patil· Aug 8, 2024

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

  • Sakshi Patil· Jul 7, 2024

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

  • Ganesh Mohane· Jun 6, 2024

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

  • Oshnikdeep· May 5, 2024

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

  • Dhruvi Jain· Apr 4, 2024

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

  • Rahul Santra· Mar 3, 2024

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

  • Pratham Ware· Feb 2, 2024

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

  • Yash Thakker· Jan 1, 2024

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