About hmdl
hmdl is an MCP server published by git+hmdl-inc in the Developer Tools category: observability SDK for MCP (Model Context Protocol) servers - Heimdall Platform. It has been installed 0 times through Conduid.
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README
hmdl - Heimdall Observability SDK for JavaScript/TypeScript
Observability SDK for MCP (Model Context Protocol) servers, built on OpenTelemetry.
Installation
npm install hmdl
# or
yarn add hmdl
# or
pnpm add hmdl
Quick Start
1. Create Organization and Project in Heimdall
Before using the SDK, you need to set up your organization and project in the Heimdall dashboard:
- Start the Heimdall backend and frontend (see Heimdall Documentation)
- Navigate to http://localhost:5173
- Create an account with your email and password
- Create an Organization - this groups your projects together
- Create a Project - each project has a unique ID for trace collection
- Go to Settings to find your Organization ID and Project ID
2. Set up environment variables
# Required for local development
export HEIMDALL_ENDPOINT="http://localhost:4318" # Your Heimdall backend
export HEIMDALL_ORG_ID="your-org-id" # From Heimdall Settings page
export HEIMDALL_PROJECT_ID="your-project-id" # From Heimdall Settings page
export HEIMDALL_ENABLED="true"
# Optional
export HEIMDALL_SERVICE_NAME="my-mcp-server"
export HEIMDALL_ENVIRONMENT="development"
# For production (with API key)
export HEIMDALL_API_KEY="your-api-key"
export HEIMDALL_ENDPOINT="https://api.heimdall.dev"
3. Initialize the client
import { HeimdallClient } from 'hmdl';
// Initialize (uses environment variables by default)
const client = new HeimdallClient();
// Or with explicit configuration
const client = new HeimdallClient({
endpoint: 'http://localhost:4318',
orgId: 'your-org-id', // From Settings page
projectId: 'your-project-id', // From Settings page
serviceName: 'my-mcp-server',
environment: 'development',
});
4. Instrument your MCP tool functions
Using wrapper functions
import { traceMCPTool } from 'hmdl';
const searchDocuments = traceMCPTool(
async (query: string, limit: number = 10) => {
// Your implementation here
return results;
},
{ name: 'search-documents', paramNames: ['query', 'limit'] }
);
const anotherTool = traceMCPTool(
async (data: Record<string, unknown>) => {
return { processed: true, ...data };
},
{ name: 'another-tool', paramNames: ['data'] }
);
Using TypeScript decorators
import { HeimdallClient, MCPTool } from 'hmdl';
// Initialize client first
new HeimdallClient();
class MyMCPServer {
@MCPTool()
async searchDocuments(query: string, limit: number = 10) {
// Your implementation
return results;
}
@MCPTool({ name: 'custom-tool-name' })
async anotherTool(data: unknown) {
return processedData;
}
}
5. Flush on shutdown
// Ensure spans are flushed before exit
process.on('beforeExit', async () => {
await client.flush();
});
// Or for graceful shutdown
process.on('SIGTERM', async () => {
await client.shutdown();
process.exit(0);
});
Configuration
| Environment Variable | Description | Default |
|---|---|---|
HEIMDALL_ENDPOINT |
Heimdall backend URL | http://localhost:4318 |
HEIMDALL_ORG_ID |
Organization ID (from Settings page) | default |
HEIMDALL_PROJECT_ID |
Project ID (from Settings page) | default |
HEIMDALL_ENABLED |
Enable/disable tracing | true |
HEIMDALL_SERVICE_NAME |
Service name for traces | mcp-server |
HEIMDALL_ENVIRONMENT |
Deployment environment | development |
HEIMDALL_API_KEY |
API key (optional for local dev) | - |
HEIMDALL_DEBUG |
Enable debug logging | false |
HEIMDALL_BATCH_SIZE |
Spans per batch | 100 |
HEIMDALL_FLUSH_INTERVAL_MS |
Flush interval (ms) | 5000 |
HEIMDALL_SESSION_ID |
Default session ID | - |
HEIMDALL_USER_ID |
Default user ID | - |
Local Development
For local development, you don't need an API key. Just set:
export HEIMDALL_ENDPOINT="http://localhost:4318"
export HEIMDALL_ORG_ID="your-org-id" # Copy from Settings page
export HEIMDALL_PROJECT_ID="your-project-id" # Copy from Settings page
export HEIMDALL_ENABLED="true"
Advanced Usage
Session and User Tracking
traceMCPTool automatically includes session and user IDs in spans. You just need to provide them via one of these methods:
Option 1: HTTP Headers (Recommended for MCP servers)
Pass HTTP headers directly to traceMCPTool. Session ID is extracted from the Mcp-Session-Id header, and user ID from the JWT token in the Authorization header:
import { traceMCPTool } from 'hmdl';
app.post('/mcp', async (req, res) => {
const searchTool = traceMCPTool(async (query: string) => {
return results;
}, {
name: 'search',
headers: req.headers // Automatically extracts session/user
});
const result = await searchTool('test');
res.json(result);
});
Option 2: Extractors (Per-tool extraction)
const myTool = traceMCPTool(
(ctx: { sessionId?: string; userId?: string }, query: string) => {
return `Query: ${query}`;
},
{
name: 'my-tool',
// Context is the first argument (args[0])
sessionExtractor: (args) => args[0]?.sessionId,
userExtractor: (args) => args[0]?.userId,
}
);
Resolution Priority
- Extractor callback → 2. HTTP headers → 3. Client value (initialized from environment variables)
Note: If no user ID is found through any of these methods,
"anonymous"is used as the default.
Manual spans
import { HeimdallClient } from 'hmdl';
const client = new HeimdallClient();
await client.startSpan('my-operation', async (span) => {
span.setAttribute('custom.attribute', 'value');
// Your code here
return result;
});
Wrapper options
const myTool = traceMCPTool(fn, {
name: 'custom-name', // Custom span name
paramNames: ['query', 'limit'], // Parameter names for better input display
captureInput: true, // Capture function arguments (default: true)
captureOutput: false, // Don't capture return value
});
Note: The
paramNamesoption allows you to specify parameter names for better input display in the Heimdall dashboard. Without it, inputs are shown as an array. With it, inputs are shown as a named object (e.g.,{"query": "test", "limit": 10}instead of["test", 10]).
What gets tracked?
For each MCP function call, Heimdall tracks:
- Input parameters: Function arguments (serialized to JSON)
- Output/response: Return value (serialized to JSON)
- Status: Success or error
- Latency: Execution time in milliseconds
- Errors: Exception type, message, and stack trace
- Metadata: Service name, environment, timestamps
OpenTelemetry Integration
This SDK is built on OpenTelemetry, making it compatible with the broader observability ecosystem.
License
MIT License - see LICENSE for details.
README mirrored from the source repository 4 months ago. The original is authoritative.