arcade-mcp/libs/arcade-serve
Francisco Or Something 1492c80fc5
TOO-627: Improve error messages for agents and Datadog (#814)
## Summary

- Improve tool call error messages across 4 libraries (arcade-core,
arcade-tdk, arcade-mcp-server, arcade-serve) so agents can self-correct
and Datadog can facet on structured fields
- Guard empty error messages, enrich input validation errors with
field-level detail, fix `@tool` decorator fallback formatting, surface
`additional_prompt_content` in MCP responses, and add structured log
extras for Datadog
- Addresses the 3 worst error patterns: generic "Error in tool input
deserialization", bare `KeyError` values, and empty `FatalToolError`
messages

**Linear:** TOO-627
**Plan:** `docs/plans/2026-04-08-improve-error-messages-handoff.md`

## Tasks

- [ ] Task 1: Guard empty error messages (arcade-core)
- [ ] Task 2: Enrich input validation error messages (arcade-core)
- [ ] Task 3: Improve `@tool` decorator error fallback (arcade-tdk)
- [ ] Task 4: Fix MCP agent-facing error response (arcade-mcp-server)
- [ ] Task 5: Add structured log extras in BaseWorker (arcade-serve)
- [ ] Task 6: Add structured log extras in MCP server
(arcade-mcp-server)

## Test plan

- [ ] Each task has dedicated unit tests verifying the new behavior
- [ ] `make test` passes after all tasks
- [ ] `make check` (ruff + mypy) passes
- [ ] Verify the 3 worst error patterns now produce actionable messages

🤖 Generated with [Claude Code](https://claude.com/claude-code)

<!-- CURSOR_SUMMARY -->
---

> [!NOTE]
> **Medium Risk**
> Touches cross-library error formatting and logging behavior used in
production tool execution paths; while mostly additive/guardrails, it
changes agent-visible messages and Datadog log facets, which could
impact client expectations and alerting.
> 
> **Overview**
> Improves tool-call error handling across core/runtime, MCP transport,
worker transport, and the TDK to make agent-visible failures more
actionable while *reducing sensitive-data leakage*.
> 
> In `arcade-core`, empty error messages now get placeholders,
`ToolOutputFactory.fail*` defaults blank messages, and input validation
errors are rewritten as field-level summaries that intentionally omit
rejected values (avoiding Pydantic echo of secrets). The `@tool`
fallback in `arcade-tdk` no longer surfaces `str(exception)` to agents;
it returns exception *type-only* in `message` while preserving full
detail in `developer_message`.
> 
> Adds a shared `build_tool_error_log_extra` helper and updates
`arcade-serve` + `arcade-mcp-server` to emit consistent structured
WARNING logs (`error_*`, `tool_name`, optional toolkit/version) for
Datadog, while MCP error responses now append
`additional_prompt_content` and force `structuredContent=None` on
failures per spec. Includes extensive new tests and bumps package
versions (`arcade-core` 4.6.2, `arcade-tdk` 3.6.1, `arcade-mcp-server`
1.19.3, `arcade-serve` 3.2.3).
> 
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
e5c7ebcaf56176cfbd8e6d1f2b6295352abd0ec0. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-13 20:10:51 -03:00
..
arcade_serve TOO-627: Improve error messages for agents and Datadog (#814) 2026-04-13 20:10:51 -03:00
pyproject.toml TOO-627: Improve error messages for agents and Datadog (#814) 2026-04-13 20:10:51 -03:00
README.md PyPI release arcade-serve and arcade-tdk (#432) 2025-06-13 13:06:11 -07:00

Arcade Serve

Serving infrastructure for Arcade tools and workers.

Overview

Arcade Serve provides the infrastructure for serving Arcade tools:

  • FastAPI Worker: High-performance FastAPI-based worker implementation
  • MCP Server: Model Context Protocol server for tool integration
  • Core Abstractions: Base worker classes and components
  • Authentication: Auth utilities and routing
  • Runtime Management: Tool execution and lifecycle management

Installation

pip install arcade-serve

Usage

To add a toolkit to a hosted worker such as FastAPI, you can register them in the worker itself. This allows you to explicitly define which tools should be included on a particular worker.

Here is an example of adding the math toolkit (pip install arcade-math) to a FastAPI Worker:

import arcade_math
from fastapi import FastAPI
from arcade_tdk import Toolkit
from arcade_serve.fastapi import FastAPIWorker

app = FastAPI()

worker_secret = os.environ.get("ARCADE_WORKER_SECRET")
worker = FastAPIWorker(app, secret=worker_secret)

worker.register_toolkit(Toolkit.from_module(arcade_math))

Here is an example of adding the math toolkit (pip install arcade-math) to a MCP Worker

import arcade_math
from arcade_core.catalog import ToolCatalog
from arcade_serve.mcp.stdio import StdioServer

# 1. Create and populate the tool catalog
catalog = ToolCatalog()
catalog.add_module(arcade_math)


# 2. Main entrypoint
async def main():
    # Create the worker with the tool catalog
    worker = StdioServer(catalog)

    # Run the worker
    await worker.run()


if __name__ == "__main__":
    import asyncio

    asyncio.run(main())

License

MIT License - see LICENSE file for details.