3204201360
When a tool’s output TypedDict uses total=False, MCP clients reject the
response with:
```
MCP error -32602: Structured content does not match the tool's output schema
```
Note that the bug also exists for the Engine transport
(/worker/tools/execute), but since the engine doesn't validate the
output schema, the bug never surfaced. This PR addresses the problem
holistically (MCP and Engine) in preparation for a future where the
Engine transport validates output schemas.
Two bugs combined to cause this:
1. Schema: The outputSchema had no required array and declared all
fields as strict types (e.g. "type": "string"), making every field look
mandatory and non-null.
2. Serialization: model_dump() on TypedDict-derived Pydantic models
emitted None for absent optional fields. A tool returning {"name":
"hello"} produced {"name": "hello", "optional_field": null} which is a
value the schema forbids.
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Adjusts core schema generation and MCP JSON Schema conversion for
TypedDicts, affecting how tool input/output contracts are emitted and
validated across clients; mistakes could break compatibility or
validation behavior.
>
> **Overview**
> Fixes MCP/engine validation failures for `TypedDict(total=False)`
outputs by ensuring absent optional keys are **omitted from serialized
output** and that emitted schemas correctly describe **required vs
optional** keys.
>
> `arcade-core` now tracks `required_keys`/`inner_required_keys` and
per-field `nullable` in `ValueSchema`, derives required sets from
TypedDict `__required_keys__`, and unwraps `Optional[T]` to support
optional nested TypedDicts; TypedDict-derived Pydantic models now
`model_dump(exclude_unset=True)` to avoid leaking missing fields as
`null`.
>
> `arcade-mcp-server` JSON Schema conversion now emits `required` arrays
(including for arrays of objects), supports `nullable` by generating
`type: [<type>, "null"]` (and `enum` including `None`), and treats
nullable top-level objects as valid unwrapped output schemas. Adds
focused unit/end-to-end tests plus an expanded example server
demonstrating total-false, mixed required/optional, nullable, and
optional-nested TypedDict outputs, and bumps package
versions/dependencies accordingly.
>
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
53fe8365f613053599130520b75f30b614b465ca. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
|
||
|---|---|---|
| .. | ||
| arcade_mcp_server | ||
| Makefile | ||
| pyproject.toml | ||
| README.md | ||
Arcade MCP Server
Arcade MCP (Model Context Protocol) Server enables AI assistants and development tools to interact with your Arcade tools through a standardized protocol. Build, deploy, and integrate MCP servers seamlessly across different AI platforms.
Quick Links
- Quickstart Guide - Get up and running in minutes
- Walkthrough - Learn by example
- API Reference - MCPApp API documentation
Features
- 🚀 FastAPI-like Interface - Simple, intuitive API with
MCPApp - 🔧 Tool Discovery - Automatic discovery of tools in your project
- 🔌 Multiple Transports - Support for stdio and HTTP/SSE
- 🤖 Multi-Client Support - Works with Claude, Cursor, and more
- 📦 Package Integration - Load installed Arcade packages
- 🔐 Built-in Security - Environment-based configuration and secrets
- 🔄 Hot Reload - Development mode with automatic reloading
- 📊 Production Ready - Deploy with Docker, systemd, PM2, or cloud platforms
Getting Started
Installation
pip install arcade-mcp-server
Create Your First Server
from arcade_mcp_server import MCPApp
from typing import Annotated
app = MCPApp(name="my-tools", version="1.0.0")
@app.tool
def greet(name: Annotated[str, "Name to greet"]) -> str:
"""Greet someone by name."""
return f"Hello, {name}!"
if __name__ == "__main__":
app.run()
Run Your Server
# For development
python my_tools.py
# For Claude Desktop
python -m arcade_mcp_server stdio
# For HTTP clients
python -m arcade_mcp_server --host 0.0.0.0 --port 8080
Community
Analytics & Privacy
Arcade MCP Server collects anonymous usage data to help us improve the service and debug issues. We track "MCP server start" events to understand server usage patterns and reliability.
What We Track
When the server starts, we collect the following information:
- Server configuration: transport type (
httporstdio), host, port - Server metadata: tool count, server version
- Runtime environment: Python version, OS type and release
- Timing: device timestamp
- Errors: error messages (if startup fails)
Privacy
- For anonymous users: Events are tracked with an anonymous ID and no user profile is created
- For authenticated users: Events are linked to your account to help us provide better support
- No sensitive data (credentials, tool inputs/outputs, or personal information) is ever collected
Opt Out
To disable usage tracking, set the environment variable ARCADE_USAGE_TRACKING to 0.
License
Arcade MCP Server is open source software licensed under the MIT license.