Observability and Incident MCP Servers

Find MCP servers that help agents inspect alerts, logs, traces, errors, dashboards, and production incidents across observability tools.

对比服务器搜索 Incident response

匹配的 MCP 服务器

结果来自现有 MCP Servers 目录，没有单独的主题数据库。

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Datadog MCP Server
Provides comprehensive Datadog monitoring capabilities through MCP clients. Requires Datadog API and Application keys.
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Datadog MCP Server
Provides comprehensive Datadog monitoring capabilities through any MCP client.
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Datadog MCP Server
An MCP server for the Datadog API, allowing you to search logs and traces.
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mcp-datadog-server
Datadog MCP Server
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Sentry MCP Server
An MCP server for interacting with the Sentry error tracking and performance monitoring platform.
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Sentry MCP
官方
Official Sentry MCP server for investigating issues, error reports, traces, and performance monitoring data from AI coding agents.
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Multi Sentry MCP
Multi-org Sentry MCP server — isolated error monitoring across multiple projects from a single config. Process-level security, handoff package generation.
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observability-mcp
One MCP server that connects to any observability backend through pluggable connectors, normalizes the data, adds intelligent analysis, and provides a web UI for configuration.
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Agent Evals by Galileo
官方
Bring agent evaluations, observability, and synthetic test set generation directly into your IDE for free with Galileo's new MCP server
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Digma
官方
A code observability MCP enabling dynamic code analysis based on OTEL/APM data to assist in code reviews, issues identification and fix, highlighting risky code etc.
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Elementary
官方
Expose data observability, lineage, test results & incidents to AI agents via MCP
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Ingero
eBPF-based GPU causal observability agent with MCP server. Traces CUDA Runtime/Driver APIs via uprobes and host kernel events via tracepoints to build causal chains explaining GPU latency. 7 MCP tools for AI-assisted GPU debugging and root cause analysis. <2% overhead, production-safe.
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Incident Response MCP 适合的场景

Let agents inspect errors, alerts, dashboards, and recent deploy context during an incident.

Summarize production signals before deciding whether to rollback, patch, or escalate.

Connect monitoring context to coding and infrastructure workflows without pasting logs by hand.

设置清单

  1. 1Choose servers for the observability tools your team already relies on.
  2. 2Start with read-only access to alerts, dashboards, logs, traces, and error details.
  3. 3Add credentials to the MCP client with tightly scoped permissions.
  4. 4Test with a known historical issue before using the setup during a live incident.

如何选择

  • Prefer source links, timestamps, filters, and scoped query controls.
  • Check whether the server exposes enough context for the agent to distinguish symptoms from causes.
  • Keep remediation actions separate from observation unless your approval flow is explicit.

Incident Response MCP 常见问题

What is Observability MCP used for?

It gives agents access to operational signals such as alerts, logs, traces, dashboards, and errors so they can help summarize and investigate incidents.

Should an incident MCP server be able to change production?

Usually no. Start with read-only observability. If you expose remediation actions, put them behind explicit approval and logging.

Which tools fit this topic?

Datadog, Sentry, Grafana, log search, tracing tools, uptime monitors, and alerting systems all fit when the workflow is incident investigation.