# PR Description
Consider this PR the result of a full pass through of this repository.
## Add helper for adding tools to an `MCPApp`
You can now add all of the tools in a module to an `MCPApp` via
`app.add_tools_from_module(...)`
## Edit what `arcade new` generates
First, I updated the backend to use hatchling.
Second, the structure generated before this PR was simple, but did not
create a proper Python module.
This hindered developers in the following ways:
1. Difficult to add the tools in your server to an evaluation suite
2. Difficult to add more than one tool to an MCPApp at a time
3. All other niceties that come with being able to import modules
```
# Before
server/
├── .env.example
├── server.py
└── pyproject.toml
```
This PR updates the structure generated such that a valid Python module
is generated:
```
# After
server/
├── pyproject.toml
└── src/
└── server/
├── __init__.py
├── .env.example
└── server.py
```
## Fix Tool Chaining
`self._ctx.server.executor.run(...)` was being called, but `MCPServer`
does not have an instance of `ToolExecutor` (and it's not intended to be
an instance anyways). I updated `Tool.call_raw` to pass the programmatic
tool call through the `MCPServer._handle_call_tool`. This means that the
programmatic tool calls now go through the same steps that a typical
tool call (initiated by the MCP client) would.
This means that **toolA**, which specifies **requirementsA**, is
permitted to call **toolB**, which specifies **requirementsB**, without
needing to explicitly declare or satisfy **requirementsB**. I believe
this is acceptable because the secrets and/or auth token associated with
**toolB's** `Context` are not exposed to **toolA**, and the secrets
and/or auth token associated with **toolA's** `Context` are not exposed
to **toolB**.
## Fix User Elicitation
1. The read & write streams were created with a maximum queue size of 0.
I increased this to 100.
2. I updated `ServerSession`'s run loop to both read messages from the
stream & process them concurrently. This enables server initiated
requests (like user elicitation and progress reporting) to be handled
while tools are being executed. Otherwise, the server initiated requests
would wait for the tool to finish executing and the tool execution would
wait for the server initiated request to finish.
3.
## Fix Progress Reporting
Progress tokens sent by the client were not being stored. Therefore
there was no way to notify a client with progress updates. I am now
storing the `progressToken`, along with other `_meta` sent from the
client, in the `ServerSession`'s `_request_meta`. I am setting
`_request_meta` whenever the `MCPServer` is handling an incoming message
from a client.
## Fix handling of server names with spaces
Before:
Server name: "The simple server name"
Tool name: whisper_secret
Name seen by client: "The_simple_server_name_WhisperSecret"
After
Server name: "The simple server name"
Tool name: whisper_secret
Name seen by client: "TheSimpleServerName_WhisperSecret"
## Add Integration Tests
The stdio integration test is much more comprehensive than the http
integration test. These tests will let me sleep a bit more at night
## Add Example MCP Servers
Example servers for sampling, user-elicitation, progress reporting,
logging, tool chaining, combining prebuilt tools with custom tools, tool
secrets, tool auth, evaluations, and more!
## Add Docker template
Added a Docker template for running an MCP server in Docker (and removed
the old docker stuff)
|
||
|---|---|---|
| .github | ||
| .vscode | ||
| contrib | ||
| docker | ||
| examples | ||
| libs | ||
| schemas/preview | ||
| toolkits | ||
| .editorconfig | ||
| .gitignore | ||
| .pre-commit-config.yaml | ||
| .prettierignore | ||
| .prettierrc.toml | ||
| .ruff.toml | ||
| CONTRIBUTING.md | ||
| cspell.config.yaml | ||
| LICENSE | ||
| Makefile | ||
| pyproject.toml | ||
| README.md | ||
| uv_setup.sh | ||
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!
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
.envfile containing a secret required by one of the generated tools inserver.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
- Discord: Join our Discord community for real-time support and discussions.
- GitHub: Contribute or report issues on the Arcade GitHub repository.
- Documentation: Find in-depth guides and API references at Arcade Documentation.