by ArcadeAI
MCP Server Framework and Tool Development library for building custom capabilities into agents.
# Add to your Claude Code skills
git clone https://github.com/ArcadeAI/arcade-mcpLast scanned: 5/4/2026
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}arcade-mcp is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by ArcadeAI. MCP Server Framework and Tool Development library for building custom capabilities into agents. It has 924 GitHub stars.
Yes. arcade-mcp passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/ArcadeAI/arcade-mcp" and add it to your Claude Code skills directory (see the Installation section above).
arcade-mcp is primarily written in Python. It is open-source under ArcadeAI on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh arcade-mcp against similar tools.
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Open-source Python framework for building MCP servers and tools.
Documentation • Examples • Discord
arcade-mcp is the Python framework for building Model Context Protocol servers and the tools that run inside them. It powers the 7,500+ prebuilt tools across 81 MCP servers at Arcade.dev, and is open-sourced so you can build your own.
Use it when you need MCP tools that aren't already in the prebuilt catalog: internal APIs, custom OAuth providers, domain-specific integrations.
Highlights:
requires_auth=GitHub(scopes=["repo"]) and Arcade handles OAuth, token refresh, and per-call scoping. The client and the LLM never see the token.arcade evals for testing tool-call accuracy against real LLMs.arcade deploy for one-command hosting on Arcade Cloud.Tools can declare:
The secrets (OAuth tokens, API keys, etc) are securely injected by Arcade into your tool call at runtime, so that your tool can authorize requests to upstream APIs, for example. The client and the LLM never see the secret values.
A tool that reads the user's GitHub repos is one decorator away:
from arcade_mcp_server import MCPApp, Context
from arcade_mcp_server.auth import GitHub
app = MCPApp(name="gh", version="1.0.0")
@app.tool(requires_auth=GitHub(scopes=["repo"]))
async def list_my_repos(context: Context) -> list[str]:
"""List the authenticated user's GitHub repositories."""
token = context.get_auth_token_or_empty()
...
When the tool is invoked through Arcade Cloud, the user is presented with a URL to complete the OAuth challenge in their browser. On success, the token is injected into context for that call. Subsequent calls reuse and refresh the token automatically.
22 helper classes ship with the framework for popular providers:
Asana, Atlassian, Attio, ClickUp, Discord, Dropbox, Figma, GitHub, Google, Hubspot, Linear, LinkedIn, Microsoft, Notion, PagerDuty, Reddit, Slack, Spotify, Twitch, X, Zoom.
For any other OAuth API, use the generic OAuth2(...) class and register your OAuth app in the Arcade Dashboard.
uv tool install arcade-mcp
arcade new my_server
cd my_server/src/my_server
The scaffold creates pyproject.toml, .env.example, and a server.py with example tools.
A minimal tool:
from typing import Annotated
from arcade_mcp_server import MCPApp
app = MCPApp(name="my_server", version="1.0.0")
@app.tool
def greet(name: Annotated[str, "Name to greet"]) -> str:
"""Greet a person by name."""
return f"Hello, {name}!"
if __name__ == "__main__":
app.run(transport="stdio")
uv run server.py # stdio (default), for Claude Desktop and CLI tools
uv run server.py http # HTTP+SSE, for Cursor and VS Code; docs at http://127.0.0.1:8000/docs
arcade configure claude # Claude Desktop, stdio
arcade configure cursor --transport http --port 8080 # Cursor, local HTTP on :8080
arcade configure vscode --entrypoint my_server.py # VS Code, stdio launching my_server.py
For more patterns (MCP resources, sampling, progress reporting, tool chaining, end-to-end agents, eval suites, Resource Server Auth), browse examples/mcp_servers/. Run arcade --help for the full CLI.
arcade login followed by arcade deploy packages your server, discovers and upserts required secrets, and polls until it's healthy on Arcade Cloud. From there, the Arcade Engine fulfills authorized tool calling flows for end users, and arcade server logs/list/status plus arcade dashboard provide observability and management.
Standalone is supported too. Run your server in any MCP client over stdio or HTTP. Supply your own access tokens for tools with requires_auth=..., and protect production HTTP endpoints with Resource Server Auth (OAuth 2.1 Bearer tokens validated against your IdP).
Requires Python 3.10+ and uv.
git clone https://github.com/ArcadeAI/arcade-mcp.git
cd arcade-mcp
make install
See CONTRIBUTING.md for development workflow and SECURITY.md for vulnerability reporting.
MIT. See LICENSE.