Versions:
* arcade-mcp\==1.0.0rc1
* arcade-mcp-server\==1.0.0rc1
* arcade-core\==2.5.0rc1
* arcade-tdk\==2.6.0rc1
* arcade-serve\==2.2.0rc1
### Summary
Adds first-class MCP support across Arcade, introduces a new MCP server
and CLI, unifies the project under the arcade-mcp name, overhauls
templates/scaffolding, and improves developer tooling, secrets
management, and examples.
### Highlights
- **MCP Server & Core**
- New MCP server with stdio and HTTP/SSE transports, session management,
resumability, and lifecycle handling.
- FastAPI-like `MCPApp` for building servers with lazy init; integrated
worker+MCP HTTP app option.
- Middleware system (logging and error handling), robust exception
hierarchy, and Pydantic-based settings.
- Async-safe managers for tools, resources, and prompts backed by
registries and locks.
- Developer-facing, transport-agnostic runtime context interfaces (logs,
tools, prompts, resources, sampling, UI, notifications).
- Conversion from Arcade ToolDefinition to MCP tool schema; OpenAI JSON
tool schema converter.
- Parser supports `@app.tool`/`@app.tool(...)` decorators.
- **CLI**
- New `mcp` command to run MCP servers with stdio or HTTP/SSE.
- New `secret` command to set/list/unset tool secrets (supports .env
input, preserves original casing for lookups).
- `new` command refactored; option to create a full toolkit package with
scaffolding.
- `chat` command removed.
- `serve.py` imports updated to `arcade_serve.fastapi.telemetry`;
version retrieval now uses `arcade-mcp`.
- `show.py` refactor to use new local catalog utilities.
- `display_tool_details` improved: adds “Default” column and handles
nested properties.
- **Configuration & Discovery**
- New `configure.py` to set up Claude Desktop, Cursor, and VS Code to
connect to local or Arcade Cloud MCP servers.
- Discovery utilities to find/install toolkits, build `ToolCatalog`s,
analyze files for tools, load kits from directories (pyproject parsing),
and build minimal toolkits.
- Better handling of provider API key resolution and evaluation suite
loading.
- **Templates & Scaffolding**
- Reorganized template structure (minimal vs full); moved
`.pre-commit-config.yaml`, `.ruff.toml`, license, Makefile, README,
tests, and tools layout to correct paths.
- Minimal template adds `.env.example` for runtime secret injection.
- Template pyproject updated for MCP servers; includes sample server
with greeting and secret-reveal tools.
- Authorization flow in templates simplified.
- **Repo-wide Renaming & Examples**
- Migrates references from `arcade-ai` to `arcade-mcp` across READMEs,
scripts, and package metadata.
- Examples updated (LangChain/LangGraph/AI SDK/TypeScript) and package
name changed to `arcade-mcp-sdk`.
- **Evals & Core Utilities**
- Evals now use OpenAI tooling format (`OpenAIToolList`, `to_openai`);
`tool_eval` takes `provider_api_key`.
- Core utilities: fixed `does_function_return_value` by dedenting before
parse; version bump to `2.5.0rc1` and dependency cleanup.
- **Tooling & CI**
- `setup-uv-env` action splits toolkit vs contrib dependency
installation.
- Pre-commit: excludes `libs/arcade-mcp-server/mkdocs.yml` and
`libs/tests/` from YAML and Ruff hooks; Ruff per-file ignores (e.g.,
C901 in `libs/**/*.py`, TRY400 in server docs paths).
- Makefile updates for uv env setup, quality checks, tests, builds, and
new `shell` target.
- Added Makefile to MCP server library to streamline dev workflow.
- **Cleanup**
- Removed `claude.json` config.
- Simplified stdio entrypoint; removed unused imports (`arcade_gmail`,
`arcade_search`).
### Breaking Changes
- **CLI**: `chat` command removed; use `mcp`, `secret`, and updated
`new`.
- **Naming**: All users should update references from `arcade-ai` to
`arcade-mcp`.
- **Templates**: File paths moved; downstream scripts referencing old
template locations may need updates.
### Getting Started
- Run an MCP server:
- `arcade mcp --stdio --toolkits your_toolkit`
- `arcade mcp --http --toolkits your_toolkit`
- Manage secrets:
- `arcade secret set your_toolkit KEY=value`
- `arcade secret list your_toolkit`
- `arcade secret unset your_toolkit KEY`
- Configure clients:
- `arcade configure` to set up Claude Desktop, Cursor, and VS Code for
local/Arcade Cloud MCP.
---------
Co-authored-by: Sam Partee <sam@arcade-ai.com>
Co-authored-by: Shub <125150494+shubcodes@users.noreply.github.com>
# Improvements to Arcade TDK Error Handling
I tried my very best to not make any breaking changes in this PR. So,
you will notice various "Deprecation" notices throughout.
### Instructions for PR reviewers
1. Pull down this PR's branch
2. Pull down the Engine's tool error handling PR's branch
3. Update your installed arcadepy to have the following:
- In `arcadepy/resources/tools/tools.py`, if you want to test out
including stacktraces, then you need to update `ToolsResource.execute`
to accept a `include_error_stacktrace` argument and also include the
"include_error_stacktrace" argument to the POST to the Engine inside of
the function's execute method's body.
- In `arcadepy/types/execute_tool_response.py` add the following enum
```py
class ErrorKind(str, Enum):
"""Error kind that is comprised of
- the who (toolkit, tool, upstream)
- the when (load time, definition parsing time, runtime)
- the what (bad_definition, bad_input, bad_output, retry,
context_required, fatal, etc.)"""
TOOLKIT_LOAD_FAILED = "TOOLKIT_LOAD_FAILED"
TOOL_DEFINITION_BAD_DEFINITION = "TOOL_DEFINITION_BAD_DEFINITION"
TOOL_DEFINITION_BAD_INPUT_SCHEMA = "TOOL_DEFINITION_BAD_INPUT_SCHEMA"
TOOL_DEFINITION_BAD_OUTPUT_SCHEMA = "TOOL_DEFINITION_BAD_OUTPUT_SCHEMA"
TOOL_RUNTIME_BAD_INPUT_VALUE = "TOOL_RUNTIME_BAD_INPUT_VALUE"
TOOL_RUNTIME_BAD_OUTPUT_VALUE = "TOOL_RUNTIME_BAD_OUTPUT_VALUE"
TOOL_RUNTIME_RETRY = "TOOL_RUNTIME_RETRY"
TOOL_RUNTIME_CONTEXT_REQUIRED = "TOOL_RUNTIME_CONTEXT_REQUIRED"
TOOL_RUNTIME_FATAL = "TOOL_RUNTIME_FATAL"
UPSTREAM_RUNTIME_BAD_REQUEST = "UPSTREAM_RUNTIME_BAD_REQUEST"
UPSTREAM_RUNTIME_AUTH_ERROR = "UPSTREAM_RUNTIME_AUTH_ERROR"
UPSTREAM_RUNTIME_NOT_FOUND = "UPSTREAM_RUNTIME_NOT_FOUND"
UPSTREAM_RUNTIME_VALIDATION_ERROR = "UPSTREAM_RUNTIME_VALIDATION_ERROR"
UPSTREAM_RUNTIME_RATE_LIMIT = "UPSTREAM_RUNTIME_RATE_LIMIT"
UPSTREAM_RUNTIME_SERVER_ERROR = "UPSTREAM_RUNTIME_SERVER_ERROR"
UPSTREAM_RUNTIME_UNMAPPED = "UPSTREAM_RUNTIME_UNMAPPED"
UNKNOWN = "UNKNOWN"
```
- In `arcadepy/types/execute_tool_response.py` add the following fields
to OutputError:
```py
kind: ErrorKind
status_code: Optional[int] = None
stacktrace: Optional[str] = None
extra: Optional[dict[str, Any]] = None
```
### Example Client Usage
```py
# Example of handling an upstream rate limit
error = response.output.error
if error and error.kind == ErrorKind.UPSTREAM_RUNTIME_RATE_LIMIT:
sleep_time = error.retry_after_ms / 1000
time.sleep(sleep_time)
# and then execute again
```
```py
# Examples of determining what type of runtime error it is
error = response.output.error
if error:
is_retryable_error = error.kind == ErrorKind.TOOL_RUNTIME_RETRY
is_a_bug_in_the_tool = error.kind == ErrorKind.TOOL_RUNTIME_FATAL
is_additional_context_required = error.kind == ErrorKind.TOOL_RUNTIME_CONTEXT_REQUIRED
```
### Example Tool Usage
```py
# EXAMPLE 1 letting Arcade handle upstream error handling for you
reddit_client.post(params) # Arcade's httpx adapter will handle error handling for you!
# ------------------------------------
# EXAMPLE 2 handling upstream bad request yourself, but letting Arcade handle the rest
try:
reddit_client.post(params)
except httpx.HTTPStatusError as e:
if e.status_code == 400:
raise UpstreamError("My extra custom message) from e
raise
```
```py
# EXAMPLE 1 letting Arcade handle it for you
risky_element = my_risky_list[42] # Arcade will raise a FatalToolError for you
# ------------------------------------
# EXAMPLE 2 handling it yourself for extra flexibility
try:
risky_element = my_risky_list[42]
except IndexError as e:
raise FatalToolError("My extra custom message") from e
```
### Non-runtime Error Message Examples
Example ToolkitLoadError Messages:
```
- [TOOLKIT_LOAD_FAILED] ToolkitLoadError when loading toolkit 'sample_tool': Could not import module mock_module. Reason: Mock import error
- [TOOLKIT_LOAD_FAILED] ToolkitLoadError when loading toolkit 'test_toolkit': Tool 'ValidTool' in toolkit 'test_toolkit' already exists in the catalog.
```
Example ToolDefinitionError Messages
```
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_missing_description': Tool 'tool_missing_description' is missing a description
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_invalid_secret_type': Secret keys must be strings (error in tool ToolWithInvalidSecretType).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_empty_secret': Secrets must have a non-empty key (error in tool ToolWithEmptySecret).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_invalid_metadata_type': Metadata must be strings (error in tool ToolWithInvalidMetadataType).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_metadata_requiring_auth_without_auth': Tool ToolWithMetadataRequiringAuthWithoutAuth declares metadata key 'client_id', which requires that the tool has an auth requirement, but no auth requirement was provided. Please specify an auth requirement.
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_empty_metadata': Metadata must have a non-empty key (error in tool ToolWithEmptyMetadata).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_unsupported_param_type': Unsupported parameter type: <class 'test_catalog.MyFancyTestClass'>
```
Example ToolInputSchemaError Messages
```
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_missing_input_parameter_annotation': Parameter 'input_text' is missing a description
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_no_type_annotation': Parameter param has no type annotation.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_invalid_param_name': Invalid parameter name: '123invalid' is not a valid identifier. Identifiers must start with a letter or underscore, and can only contain letters, digits, or underscores.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_too_many_annotations': Parameter param: Annotated[str, 'name', 'desc', 'extra'] has too many string annotations. Expected 0, 1, or 2, got 3.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_required_union_param': Parameter param is a union type. Only optional types are supported.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_non_callable_default_factory': Default factory for parameter param: Annotated[str, 'Parameter'] = FieldInfo(annotation=NoneType, required=False, default_factory=str) is not callable.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_multiple_tool_contexts': Only one ToolContext parameter is supported, but tool tool_with_multiple_tool_contexts has multiple.
```
Example ToolOutputSchemaError Messages
```
- [TOOL_DEFINITION_BAD_OUTPUT_SCHEMA] ToolOutputSchemaError in definition of tool 'tool_missing_return_type_hint': Tool 'ToolMissingReturnTypeHint' must have a return type
- [TOOL_DEFINITION_BAD_OUTPUT_SCHEMA] ToolOutputSchemaError in definition of tool 'tool_with_unsupported_output_type': Unsupported output type '<class 'test_catalog.MyFancyTestClass'>'. Only built-in Python types, TypedDicts, Pydantic models, and standard collections are supported as tool output types.
```
### Runtime Error Message Examples
Example Tool Runtime Error Messages
```
- [TOOL_RUNTIME_FATAL] FatalToolError during execution of tool 'get_posts_in_subreddit': list index out of range
- [TOOL_RUNTIME_CONTEXT_REQUIRED] ContextRequiredToolError during execution of tool 'get_posts_in_subreddit': Ambiguous username. Please provide a more specific username
- [TOOL_RUNTIME_RETRY] RetryableToolError during execution of tool 'get_posts_in_subreddit': Retry with subreddit=learnpython or subreddit=learnprogramming
```
Example Upstream Runtime Error Messages
```
- [UPSTREAM_RUNTIME_RATE_LIMIT] UpstreamRateLimitError during execution of tool 'get_posts_in_subreddit': 429 Client Error: Too Many Requests
- [UPSTREAM_RUNTIME_BAD_REQUEST] UpstreamError during execution of tool 'get_posts_in_subreddit': 400 Client Error: Bad request. Missing 'id' parameter.
- [UPSTREAM_RUNTIME_BAD_REQUEST] UpstreamError during execution of tool 'search_files': Upstream Google API error: Invalid value '-23'. Values must be within the range: [value: 1\n, value: 1000\n]
```
## Summary
This PR removes the requirement that all toolkits must have the arcade_
prefix and introduces a more flexible toolkit discovery system using
Python entry points.
### 🏷️ Flexible Toolkit Naming
* Community toolkits: Only add arcade_ prefix when the user is in
arcade-ai/toolkits/ directory and explicitly chooses to create a
community contribution.
* External toolkits: No prefix requirement - developers can name their
toolkits however they want
* Toolkit names are now determined by user choice rather than enforced
automatically
### 🔍 Entry Point Discovery
* Added find_arcade_toolkits_from_entrypoints() method to discover
toolkits via entry points
* Entry point group: arcade_toolkits with name: toolkit_name
* Updated pyproject.toml template to include entry point configuration
* Entry point discovery takes precedence over prefix-based discovery for
deduplication
### 📦 Backward Compatibility
* Existing arcade_* prefixed toolkits continue to work via
find_arcade_toolkits_from_prefix()
find_all_arcade_toolkits() now combines both discovery methods
* Deduplication logic prefers entry point toolkits over prefix-based
ones when package names match
### 🛠️ `arcade new` Template Updates
* pyproject.toml template for `arcade new` now includes entry point
configuration: [project.entry-points.arcade_toolkits]
### 🔧 Minor Improvements
* Refactored _strip_arcade_prefix() into a separate method for
reusability
* Updated variable naming for clarity (community_toolkit →
is_community_toolkit)
### Benefits
* Developer Freedom: Toolkit developers are no longer forced to use the
arcade_ prefix. They are also no longer forced to use the package name
as the toolkit name.
* Cleaner Naming: External toolkits can use more natural names (e.g.,
my_company_toolkit instead of arcade_my_company_toolkit)
* Better Discovery: Entry points provide a more standard Python
mechanism for plugin discovery
* Flexible Distribution: Toolkits can be distributed with any package
name while still being discoverable
### Testing
* Added comprehensive tests for the new entry point functionality
* Tests cover edge cases like deduplication, error handling, and
backward compatibility
### Version Bumps
arcade-core: 2.0.0 → 2.1.0
arcade-ai: 2.0.5 → 2.1.0
This change makes the Arcade toolkit ecosystem more flexible and
developer-friendly while maintaining full backward compatibility with
existing toolkits.
---------
Co-authored-by: Mateo Torres <mateo@arcade.dev>
This is the first of a few PRs. Deploy to staging will fail until we
have `arcade-core`, `arcade-serve`, and `arcade-ai` released to PyPI.
This PR will release `arcade-core` to PyPI.
### PR Description
* Adds workflow that checks for changes in any pyproject.toml, and if
its version has changed, then tests, builds wheel, then publishes to
PyPI
* Updates the Dockerfile for our new structure
* Updates porter yamls
* Updates `make full-dist`
* Removes a couple unused workflows
Check out https://github.com/ArcadeAI/arcade-ai/actions/runs/15622059209
to see how the new workflow works (note that it failed publishing to
PyPI on purpose)
### Overview
Major restructuring from monolithic `arcade-ai` package to modular
library architecture with standardized uv-based dependency management.
### New Package Structure
- **`arcade-tdk`** - Lightweight toolkit development kit (core
decorators, auth)
- **`arcade-core`** - Core execution engine and catalog functionality
- **`arcade-serve`** - FastAPI/MCP server components
- **`arcade-ai`** - Meta package that includes CLI functionality.
Optionally include evals via the `evals` extra. Optionally include all
packages via the `all` extra.
### Key Benefits
- **Lighter Dependencies**: Toolkits now depend only on `arcade-tdk` (~2
deps) vs full `arcade-ai` (~30+ deps)
- **Faster Builds**: uv provides 10-100x faster dependency resolution
and installation
- **Better Modularity**: Clear separation of concerns, consumers import
only what they need
- **Standard Tooling**: Eliminates custom poetry scripts, uses standard
Python packaging
### Migration Impact
- All 20 toolkits converted from poetry → uv with `arcade-tdk`
dependencies plus `arcade-ai[evals]` and `arcade-serve` dev
dependencies. When developing locally, devs should install toolkits via
`make install-local`.
- Modern Python 3.10+ type hints throughout
- Standardized build system with hatchling backend
- Enhanced Makefile with robust toolkit management commands
- Removed `arcade dev` CLI command
- Reduce the number of files created by `arcade new` and add an option
to not generate a tests and evals folder.
This foundation enables faster development cycles and cleaner dependency
chains for the growing toolkit ecosystem.
### Todo After this PR is merged
- [ ] Post-merge workflow(s) (release & publish containers, etc)
- [ ] Release order plan. @EricGustin suggests releasing in the
following order:
1. `arcade-core` version 0.1.0
2. `arcade-serve` version 0.1.0 and `arcade-tdk` version 0.1.0
3. `arcade-ai` version 2.0.0
4. Patch release for all toolkits (all changes in toolkits are internal
refactors)
- [ ] [Update docs](https://github.com/ArcadeAI/docs/pull/318)
---------
Co-authored-by: Eric Gustin <eric@arcade.dev>
Co-authored-by: Eric Gustin <34000337+EricGustin@users.noreply.github.com>
