arcade-mcp/libs/arcade-mcp-server/docs/clients/cursor.md
Eric Gustin 3424ec8219
MCP Local (#563)
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>
2025-09-25 15:28:15 -07:00

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# Cursor IDE
Cursor is an AI-powered IDE that supports MCP servers. This guide will help you integrate your Arcade MCP server with Cursor for enhanced development capabilities.
## Prerequisites
- Cursor IDE installed
- Python 3.10+ installed
- `arcade-ai` package installed (`pip install arcade-ai`)
## Configuration
Cursor reads MCP server configurations from its settings. You can configure MCP servers through:
1. Cursor Settings UI
2. Configuration file
3. Workspace settings
## Basic Setup
### Method 1: Settings UI
1. Open Cursor Settings (`Cmd/Ctrl + ,`)
2. Search for "MCP" or "Model Context Protocol"
3. Add a new server configuration:
- **Name**: `arcade-tools`
- **Command**: `python -m arcade_mcp stdio`
- **Working Directory**: `/path/to/your/project`
### Method 2: Configuration File
Add to your Cursor configuration:
```json
{
"mcp.servers": {
"arcade-tools": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio"],
"cwd": "${workspaceFolder}",
"env": {
"PYTHONPATH": "${workspaceFolder}"
}
}
}
}
```
### Method 3: Workspace Settings
Create `.cursor/settings.json` in your workspace:
```json
{
"mcp.servers": {
"project-tools": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio", "--debug"],
"cwd": "${workspaceFolder}",
"env": {
"ARCADE_API_KEY": "${env:ARCADE_API_KEY}"
}
}
}
}
```
## Development Workflow
### Hot Reload Setup
For active development with automatic reload:
```json
{
"mcp.servers": {
"dev-tools": {
"command": "python",
"args": ["-m", "arcade_mcp", "--reload", "--debug"],
"cwd": "${workspaceFolder}",
"env": {
"PYTHONPATH": "${workspaceFolder}"
}
}
}
}
```
### Virtual Environment
Use a project-specific virtual environment:
```json
{
"mcp.servers": {
"project-tools": {
"command": "${workspaceFolder}/venv/bin/python",
"args": ["-m", "arcade_mcp", "stdio"],
"cwd": "${workspaceFolder}"
}
}
}
```
### Multiple Tool Sets
Configure different tool sets for different purposes:
```json
{
"mcp.servers": {
"github-tools": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio", "--tool-package", "github"],
"env": {
"GITHUB_TOKEN": "${env:GITHUB_TOKEN}"
}
},
"database-tools": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio"],
"cwd": "${workspaceFolder}/db_tools",
"env": {
"DATABASE_URL": "${env:DATABASE_URL}"
}
},
"api-tools": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio"],
"cwd": "${workspaceFolder}/api_tools"
}
}
}
```
## Integration Features
### Inline Tool Usage
Use tools directly in your code comments:
```python
# @mcp use arcade-tools.greet name="World"
# Result will appear here
def process_data(data):
# @mcp use database-tools.query sql="SELECT * FROM users"
pass
```
### Tool Discovery
View available tools in Cursor:
1. Open Command Palette (`Cmd/Ctrl + Shift + P`)
2. Type "MCP: List Tools"
3. Select your server to see available tools
### Tool Documentation
Access tool documentation:
1. Hover over tool usage in code
2. Use `Cmd/Ctrl + Click` on tool names
3. View in the MCP panel
## Advanced Configuration
### Environment-Specific Settings
Use different configurations per environment:
```json
{
"mcp.servers": {
"tools-dev": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio", "--env-file", ".env.dev"],
"cwd": "${workspaceFolder}",
"when": "${config:environment} == 'development'"
},
"tools-prod": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio", "--env-file", ".env.prod"],
"cwd": "${workspaceFolder}",
"when": "${config:environment} == 'production'"
}
}
}
```
### Task Integration
Create tasks for MCP server management:
```json
{
"version": "2.0.0",
"tasks": [
{
"label": "Start MCP Server",
"type": "shell",
"command": "python -m arcade_mcp --reload --debug",
"problemMatcher": [],
"isBackground": true
},
{
"label": "Test Tools",
"type": "shell",
"command": "python -m arcade_mcp --tool-package ${input:package} --debug",
"problemMatcher": []
}
],
"inputs": [
{
"id": "package",
"type": "promptString",
"description": "Tool package name"
}
]
}
```
### Debugging Tools
Debug your tools with Cursor's debugger:
```json
{
"version": "0.2.0",
"configurations": [
{
"name": "Debug MCP Tools",
"type": "python",
"request": "launch",
"module": "arcade_mcp",
"args": ["--debug", "--reload"],
"cwd": "${workspaceFolder}",
"env": {
"PYTHONPATH": "${workspaceFolder}"
}
}
]
}
```
## Best Practices
### Project Structure
Organize your MCP tools effectively:
```
my-project/
 .cursor/
  settings.json # Cursor-specific settings
 .env # Environment variables
 .env.example # Example environment file
 tools/
  __init__.py
  data_tools.py # Data processing tools
  api_tools.py # API interaction tools
  utils.py # Utility tools
 requirements.txt
 README.md
```
### Tool Development Tips
1. **Use Type Hints**: Enable better IDE support
```python
from typing import Annotated
@tool
def process(
data: Annotated[str, "Input data to process"],
format: Annotated[str, "Output format"] = "json"
) -> Annotated[dict, "Processed data"]:
"""Process data in the specified format."""
pass
```
2. **Provide Clear Descriptions**: Help Cursor understand tool usage
3. **Handle Errors Gracefully**: Return helpful error messages
4. **Use Logging**: Enable debug mode for troubleshooting
5. **Test Incrementally**: Use Cursor's integrated terminal
### Performance Optimization
1. **Lazy Loading**: Import heavy dependencies inside tools
2. **Cache Results**: Use caching for expensive operations
3. **Async Support**: Use async tools for I/O operations
4. **Resource Management**: Clean up resources properly
## Troubleshooting
### Common Issues
#### Tools Not Loading
1. Check Python path and virtual environment
2. Verify `arcade-ai` installation
3. Enable debug logging to see errors
4. Check for import errors in tool files
#### Permission Errors
1. Ensure proper file permissions
2. Check working directory access
3. Verify environment variable access
#### Connection Issues
1. Restart Cursor after configuration changes
2. Check for conflicting MCP servers
3. Verify stdio transport is working
### Debugging Steps
1. Enable debug mode in your configuration
2. Check Cursor's output panel for MCP logs
3. Test tools using the command line first
4. Use Cursor's Developer Tools for detailed logs
## Example: Complete Setup
Here's a full example of setting up a Cursor workspace with MCP:
1. **Create workspace structure**:
```
my-workspace/
 .cursor/
  settings.json
 .vscode/
  tasks.json
 tools/
  my_tools.py
 pyproject.toml
```
2. **Configure `.cursor/settings.json`**:
```json
{
"mcp.servers": {
"workspace-tools": {
"command": "python",
"args": ["-m", "arcade_mcp", "stdio", "--debug"],
"cwd": "${workspaceFolder}",
"env": {
"PYTHONPATH": "${workspaceFolder}"
}
}
}
}
```
3. **Create `tools/my_tools.py`**:
```python
from arcade_tdk import tool
from typing import Annotated
import json
@tool
async def format_json(
data: Annotated[str, "JSON string to format"]
) -> Annotated[str, "Formatted JSON"]:
"""Format JSON data with proper indentation."""
parsed = json.loads(data)
return json.dumps(parsed, indent=2)
@tool
def analyze_code(
file_path: Annotated[str, "Path to analyze"]
) -> Annotated[dict, "Analysis results"]:
"""Analyze Python code quality."""
# Implementation here
pass
```
4. **Restart Cursor and start using your tools!**