Prometheus
This MCP server for Prometheus, developed by LogLM, provides a bridge between AI assistants and Prometheus metrics data. It offers a structured interface to access metric schemas, metadata, and current statistical information from Prometheus instances. The server supports basic authentication and exposes metrics through a RESTful API structure. By abstracting Prometheus query complexities, it enables AI systems to easily retrieve and analyze monitoring data. This implementation is particularly useful for DevOps teams, system administrators, and data analysts who want to incorporate Prometheus metrics into AI-driven workflows for tasks such as automated system health monitoring, performance analysis, and anomaly detection.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- devops-ci
- Source
- PulseMCP
- Repository
- github.com/loglmhq/mcp-server-prometheus
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Prometheus from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.