Datadog
This Datadog MCP server by Clement Hussenot provides integration with the Datadog monitoring and observability platform, enabling AI assistants to interact with Datadog's APIs for metrics, logs, and monitoring data. Built with Go using the official MCP Go SDK and featuring OpenAPI code generation through oapi-codegen, it offers tools for accessing Datadog's monitoring capabilities with proper API key authentication and configurable site endpoints. The implementation includes comprehensive development tooling with pre-commit hooks, Spectral API linting, Docker containerization, and multi-language support through Python dependencies, making it valuable for DevOps teams and SREs who need AI-assisted monitoring workflows, incident response automation, and observability data analysis within their existing Datadog infrastructure.
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
- cloud-infra
- Source
- PulseMCP
- Repository
- github.com/believe-sa/datadog-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Datadog 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.