mcp_tools.mdc•1.21 kB
---
description: MCP Tool Implementation Guidelines
globs: src/server/**/*.py
alwaysApply: false
---
# MCP Tool Implementation Standards
## Function Signature
- Tool functions should be async
- Follow the pattern:
```python
async def tool_name(params: Dict[str, Any]) -> Dict[str, Any]:
"""Tool description.
Args:
params: Dictionary of parameters from MCP client
Returns:
Dictionary adhering to MCP protocol response format
"""
```
## Documentation Requirements
Each tool must have documentation with:
- name
- description
- parameters
- returns
Example:
```python
"""
name: list_clusters
description: Lists all available Databricks clusters
parameters: {}
returns: List of cluster objects
"""
```
## Error Handling
- All tool functions must return errors as part of the result object with `isError: true`
- Example:
```python
{
"result": None,
"isError": True,
"errorMessage": "Unable to connect to Databricks API"
}
```
## Performance Considerations
- Implement appropriate timeouts for all external calls
- Long-running operations should provide progress updates
- Handle Databricks API rate limiting and retries