MCP Infra Lens
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| HOST | No | Bind address for the HTTP transport | 127.0.0.1 |
| PORT | No | Port for the HTTP transport | 3000 |
| INFRA_LENS_DB | No | SQLite database path. Use ':memory:' for tests | ~/.mcp-infra-lens/metrics.db |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
No tools | |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Tools are mostly distinct, though analyze_server and compare_to_baseline both perform explanatory analysis of deviations, which could cause brief hesitation. snapshot vs analyze_server clearly separates raw collection from analysis.
Four tools follow a clear verb_noun pattern (analyze_server, get_history, record_baseline, compare_to_baseline). snapshot stands alone without a verb prefix, though it functions as a verb in context—minor deviation but readable.
Five tools is ideal for this focused scope: baseline lifecycle (record, compare), historical retrieval, real-time analysis, and raw capture. Each serves a specific step in the monitoring workflow without bloat.
Covers the core monitoring lifecycle: establishing baselines, recording current state, historical lookup, and comparative analysis. Minor gaps exist (no list_baselines or delete_baseline), but agents can work around these.