Prometheus
This MCP server, developed by CaesarYangs, enables AI assistants to interact with Prometheus metrics through a standardized interface. It provides tools for querying and analyzing time-series data from Prometheus instances via the Prometheus API. The server abstracts away complexities of metric retrieval and offers a simplified workflow for AI systems to access and reason about system and application performance data. By connecting AI capabilities with Prometheus' powerful monitoring and alerting toolkit, this implementation empowers AI assistants to perform tasks like anomaly detection, capacity planning, or troubleshooting. It is particularly useful for applications requiring real-time metrics analysis, infrastructure monitoring, or any scenario where an AI system needs to understand and act on the operational state of complex distributed systems.
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 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- monitoring
- Source
- PulseMCP
- Repository
- github.com/caesaryangs/prometheus_mcp_server
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
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.