Logging lets your server send debug/info/warning/error messages to MCP clients while handling a request. This is helpful for visibility during tool execution and for debugging.
Note: Clients decide how (or whether) to display these logs.
Basic usage
from dedalus_mcp import get_context, tool
@tool(description="Process data")
async def process(data: str) -> str:
ctx = get_context()
await ctx.info("Processing", data={"bytes": len(data)})
# ... your work ...
await ctx.info("Processing complete")
return "done"
Log levels
await ctx.debug("Detailed debugging info")
await ctx.info("General operational messages")
await ctx.warning("Warning conditions")
await ctx.error("Error conditions")
| Method | Level | Use case |
|---|
ctx.debug() | DEBUG | Detailed debugging information |
ctx.info() | INFO | General operational messages |
ctx.warning() | WARNING | Warning conditions |
ctx.error() | ERROR | Error conditions |
Example: Data pipeline
from dedalus_mcp import get_context, tool
@tool(description="Run data pipeline")
async def run_pipeline(source: str) -> dict:
ctx = get_context()
await ctx.info("Starting pipeline", data={"source": source})
# Load
await ctx.debug("Loading data...")
data = load_data(source) # your code
await ctx.info("Loaded records", data={"count": len(data)})
# Transform
await ctx.debug("Transforming data...")
try:
transformed = transform(data) # your code
except ValueError as e:
await ctx.warning("Transform warning", data={"error": str(e)})
transformed = fallback_transform(data) # your code
# Save
await ctx.debug("Saving results...")
try:
save(transformed) # your code
await ctx.info("Pipeline complete", data={"records": len(transformed)})
except OSError as e:
await ctx.error("Save failed", data={"error": str(e)})
raise
return {"records": len(transformed)}
Example: Batch processing
from dedalus_mcp import get_context, tool
@tool(description="Process items in batch")
async def batch_process(items: list[str]) -> dict:
ctx = get_context()
results = {"success": 0, "failed": 0}
await ctx.info("Starting batch", data={"items": len(items)})
for i, item in enumerate(items, start=1):
await ctx.debug("Processing item", data={"index": i, "total": len(items), "item": item})
try:
process_item(item) # your code
results["success"] += 1
except Exception as e:
await ctx.warning("Item failed", data={"item": item, "error": str(e)})
results["failed"] += 1
if results["failed"]:
await ctx.warning("Batch completed with failures", data=results)
else:
await ctx.info("Batch completed successfully", data=results)
return results
Structured logging
Pass structured fields using data=:
await ctx.info(
"Request processed",
data={
"duration_ms": 150,
"items_processed": 42,
},
)
Tip: Avoid using the key "msg" inside data—Dedalus MCP uses "msg" internally for the main message text. Last modified on January 27, 2026