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OpenSIPS MCP Server

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by OpenSIPS

observability_generate_monitoring_compose

Generate a Docker Compose snippet for a Prometheus and Grafana monitoring stack that scrapes OpenSIPS metrics. Configure deployment name, ports, Grafana admin password, and external Docker network for side-car deployment.

Instructions

Generate a docker-compose snippet for a Prometheus + Grafana side-car.

The stack assumes the OpenSIPS service is on the same external Docker network so Prometheus can scrape opensips:8888/prometheus.

Parameters

deployment_name: Used in container names so multiple deployments coexist. grafana_port, prometheus_port: External ports to publish. grafana_admin_password: Set the Grafana admin password (default admin). network: External Docker network name. Create with docker network create <name> before starting the stack.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deployment_nameNoopensips
grafana_portNo
prometheus_portNo
grafana_admin_passwordNoadmin
networkNoopensips-net

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Transparent about generating a docker-compose snippet, with no annotations. Does not mention destructive effects, but as a code generator it is inherently safe and read-only.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with a brief header, assumption note, and parameter list. Every sentence adds value; no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers functionality and parameters well. Since an output schema exists, return value explanation is not needed. Could mention output format but optional.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description provides clear explanations for all 5 parameters, explaining their purposes (container names, ports, password, network) and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it generates a docker-compose snippet for a Prometheus + Grafana side-car, distinguishing it from sibling observability tools that generate bundles or dashboards.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides assumptions about network setup but does not explicitly state when to use this tool vs alternatives like observability_generate_bundle or observability_generate_dashboards.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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