ArcadeAI

arcade mcp

Built by ArcadeAI 834 stars

What is arcade mcp?

The best way to create, deploy, and share MCP Servers

How to use arcade mcp?

1. Install a compatible MCP client (like Claude Desktop). 2. Open your configuration settings. 3. Add arcade mcp using the following command: npx @modelcontextprotocol/arcade-mcp 4. Restart the client and verify the new tools are active.
🛡️ Scoped (Restricted)
npx @modelcontextprotocol/arcade-mcp --scope restricted
🔓 Unrestricted Access
npx @modelcontextprotocol/arcade-mcp

Key Features

Native MCP Protocol Support
Real-time Tool Activation & Execution
Verified High-performance Implementation
Secure Resource & Context Handling

Optimized Use Cases

Extending AI models with custom local capabilities
Automating system workflows via natural language
Connecting external data sources to LLM context windows

arcade mcp FAQ

Q

Is arcade mcp safe?

Yes, arcade mcp follows the standardized Model Context Protocol security patterns and only executes tools with explicit user-granted permissions.

Q

Is arcade mcp up to date?

arcade mcp is currently active in the registry with 834 stars on GitHub, indicating its reliability and community support.

Q

Are there any limits for arcade mcp?

Usage limits depend on the specific implementation of the MCP server and your system resources. Refer to the official documentation below for technical details.

Official Documentation

View on GitHub
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Arcade MCP Server Framework

  • To see example servers built with Arcade MCP Server Framework (this repo), check out our examples

  • To learn more about the Arcade MCP Server Framework (this repo), check out our Arcade MCP documentation

  • To learn more about other offerings from Arcade.dev, check out our documentation.

Pst. hey, you, give us a star if you like it!

<a href="https://github.com/ArcadeAI/arcade-mcp"> <img src="https://img.shields.io/github/stars/ArcadeAI/arcade-mcp.svg" alt="GitHub stars"> </a>

Quick Start: Create a New Server

The fastest way to get started is with the arcade new CLI command, which creates a complete MCP server project:

# Install the CLI
uv tool install arcade-mcp

# Create a new server project
arcade new my_server

# Navigate to the project
cd my_server/src/my_server

This generates a project with:

  • server.py - Main server file with MCPApp and example tools

  • pyproject.toml - Dependencies and project configuration

  • .env.example - Example .env file containing a secret required by one of the generated tools in server.py

The generated server.py includes proper command-line argument handling and three example tools:

#!/usr/bin/env python3
"""simple_server MCP server"""

import sys
from typing import Annotated

import httpx
from arcade_mcp_server import Context, MCPApp
from arcade_mcp_server.auth import Reddit

app = MCPApp(name="simple_server", version="1.0.0", log_level="DEBUG")


@app.tool
def greet(name: Annotated[str, "The name of the person to greet"]) -> str:
    """Greet a person by name."""
    return f"Hello, {name}!"


# To use this tool locally, you need to either set the secret in the .env file or as an environment variable
@app.tool(requires_secrets=["MY_SECRET_KEY"])
def whisper_secret(context: Context) -> Annotated[str, "The last 4 characters of the secret"]:
    """Reveal the last 4 characters of a secret"""
    # Secrets are injected into the context at runtime.
    # LLMs and MCP clients cannot see or access your secrets
    # You can define secrets in a .env file.
    try:
        secret = context.get_secret("MY_SECRET_KEY")
    except Exception as e:
        return str(e)

    return "The last 4 characters of the secret are: " + secret[-4:]

# To use this tool locally, you need to install the Arcade CLI (uv tool install arcade-mcp)
# and then run 'arcade login' to authenticate.
@app.tool(requires_auth=Reddit(scopes=["read"]))
async def get_posts_in_subreddit(
    context: Context, subreddit: Annotated[str, "The name of the subreddit"]
) -> dict:
    """Get posts from a specific subreddit"""
    # Normalize the subreddit name
    subreddit = subreddit.lower().replace("r/", "").replace(" ", "")

    # Prepare the httpx request
    # OAuth token is injected into the context at runtime.
    # LLMs and MCP clients cannot see or access your OAuth tokens.
    oauth_token = context.get_auth_token_or_empty()
    headers = {
        "Authorization": f"Bearer {oauth_token}",
        "User-Agent": "{{ toolkit_name }}-mcp-server",
    }
    params = {"limit": 5}
    url = f"https://oauth.reddit.com/r/{subreddit}/hot"

    # Make the request
    async with httpx.AsyncClient() as client:
        response = await client.get(url, headers=headers, params=params)
        response.raise_for_status()

        # Return the response
        return response.json()

# Run with specific transport
if __name__ == "__main__":
    # Get transport from command line argument, default to "stdio"
    # - "stdio" (default): Standard I/O for Claude Desktop, CLI tools, etc.
    #   Supports tools that require_auth or require_secrets out-of-the-box
    # - "http": HTTPS streaming for Cursor, VS Code, etc.
    #   Does not support tools that require_auth or require_secrets unless the server is deployed
    #   using 'arcade deploy' or added in the Arcade Developer Dashboard with 'Arcade' server type
    transport = sys.argv[1] if len(sys.argv) > 1 else "stdio"

    # Run the server
    app.run(transport=transport, host="127.0.0.1", port=8000)

This approach gives you:

  • Complete Project Setup - Everything you need in one command

  • Best Practices - Proper dependency management with pyproject.toml

  • Example Code - Learn from working examples of common patterns

  • Production Ready - Structured for growth and deployment

Running Your Server

Run your server directly with Python:

# Run with stdio transport (default)
uv run server.py

# Run with http transport via command line argument
uv run server.py http

# Or use python directly
python server.py http
python server.py stdio

Your server will start and listen for connections. With HTTP transport, you can access the API docs at http://127.0.0.1:8000/docs.

Configure MCP Clients

Once your server is running, connect it to your favorite AI assistant:

arcade configure claude # Configure Claude Desktop to connect to your stdio server in your current directory
arcade configure cursor --transport http --port 8080 # Configure Cursor to connect to your local HTTP server on port 8080
arcade configure vscode --entrypoint my_server.py # Configure VSCode to connect to your stdio server that will run when my_server.py is executed directly

Installing this Repo from Source

git clone https://github.com/ArcadeAI/arcade-mcp.git && cd arcade-mcp && make install

Support and Community

Global Ranking

-
Trust ScoreMCPHub Index

Based on codebase health & activity.

Manual Config

{ "mcpServers": { "arcade-mcp": { "command": "npx", "args": ["arcade-mcp"] } } }