What is Honeycomb MCP?
Honeycomb MCP is an implementation of the Model Context Protocol (MCP), an open standard that enables seamless communication between AI assistants and external data sources. Honeycomb’s hosted MCP server lets agents directly query, analyze, and visualize your observability data—including traces, triggers, and SLOs—using natural language.What Can You Do With Honeycomb MCP?
Honeycomb MCP gives AI agents and assistants access to Honeycomb’s observability data and metadata, so they can:- Run queries across traces, metrics, and logs
- Use BubbleUp to investigate unusual behavior in query results
- Check the state of Triggers and SLOs
- Analyze and identify patterns, anomalies, and errors
- Suggest instrumentation improvements or optimizations
- Create new Boards to record investigations
Key Features
Use Honeycomb in Your CLI, IDE, or Other Agent Interfaces
Use Honeycomb from the tools you already rely on, like your IDE, CLI, or AI assistants. Task agents to:- Investigate and remediate performance issues or bugs
- Assist in migrating dashboards and alerts
- Help explore and present system data
One-Click Install
Honeycomb MCP lets teams easily onboard members via OAuth 2.1 for fast, secure setup. No API keys to share. Just configure the MCP endpoint, authorize in your browser, and you are ready to go.AI-Optimized Tooling
Honeycomb MCP offers unique tools designed with AI agents in mind. More than just a wrapper around our public API, MCP gives agents access to tools that let them fetch single traces, raw data rows, and more.Getting Started with Honeycomb MCP
To connect your agents to Honeycomb:Enable Honeycomb Intelligence
To use Honeycomb MCP, your team must be enrolled in Honeycomb Intelligence. Once your team enables Honeycomb Intelligence, you will automatically be granted access to MCP.Configure Your AI Assistant
Follow our configuration guide to connect your preferred AI assistant. We support many popular tools, including:- Cursor
- Claude Code/Desktop
- Visual Studio Code
- Amazon Q
- and many more
Put Honeycomb MCP to Work
Once connected, you can ask agents to explore data, improve instrumentation, or investigate performance anomalies using natural language. Need ideas or inspiration? To explore real-world use cases of agents using MCP with Honeycomb, visit Honeycomb MCP Example Use Cases.Sharing Feedback
Your input helps us improve Honeycomb MCP. We are especially interested in feedback about:- Tool coverage and usefulness
- Performance and response times
- Setup experience and integration complexity
- Feature requests or use case ideas
- Join our Pollinators Community Slack and share in the
#discuss-mcpchannel. - Use the
feedbacktool directly from your agent.
Next Steps
Continue your MCP journey with these focused resources:- Core Concepts: Get familiar with the core concepts behind Model Context Protocol and how Honeycomb MCP lets AI agents interact with observability data.
- Connecting AI Agents to Honeycomb MCP: Follow step-by-step instructions to connect common agents to Honeycomb MCP.
- Example Use Cases: Explore real-world use cases and tips for working with Honeycomb via MCP.
- Troubleshooting: Find solutions to common configuration issues and learn how to verify that your agent is connected and working correctly.