Honeycomb Connector for AI agents.
12 live capabilities
Query telemetry data and manage markers in your observability platform.
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Why people use Honeycomb
Honeycomb for Faster Incident Response
With this Connector, you just tell your agent to run a query on the payment dataset. It fetches the results and shows you the bottleneck in seconds. You spend less time typing and more time fixing.
What Vinkius changes
You get to talk to your telemetry data using natural language instead of manual DSL entry.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Fast Incident Response
An SRE is paged for a spike and asks the agent to run_query on the main-api dataset to find the error.
- Real-world use case 02
Deployment Tracking
A developer wants to track a release and asks the agent to use list_dataset_columns to see which fields to include in a new query.
- Real-world use case 03
Metadata Exploration
An engineer needs to know the properties of a specific data source and asks the agent to use get_dataset_details.
Complete set · 12capabilities
The complete Honeycomb capability set.
These are the exact actions your AI can choose when you ask it to work with Honeycomb.
01—04
4 capabilities in this set.
Part of 12 available through Honeycomb.
- 01 Capability
Create marker
The create_marker capability adds a timeline annotation like a deployment or maintenance window to a dataset. This helps you contextualize data spikes or planned downtime.
- 02 Capability
Get dataset details
The get_dataset_details capability retrieves metadata for a specific dataset. This helps you understand the core properties of your telemetry sources.
- 03 Capability
Get team details
The get_team_details capability retrieves information about your Honeycomb team. It provides a clear view of your organization's team configuration.
- 04 Capability
Get query result
The get_query_result capability retrieves the actual results of an executed query. Use it to pull the specific numbers or logs you need into your chat.
05—08
4 capabilities in this set.
Part of 12 available through Honeycomb.
- 05 Capability
List dataset columns
The list_dataset_columns capability lists all columns defined in a specific dataset. It's the fastest way to see what fields are available for querying.
- 06 Capability
List datasets
The list_datasets capability lists all datasets in your Honeycomb team. Use this to find the correct slugs for markers and queries.
- 07 Capability
List queries
The list_queries capability lists query specifications for a specific dataset. You can use this to see what queries have already been built.
- 08 Capability
List triggers
The list_triggers capability lists triggers defined for a dataset. It lets you see all active alerts for a specific data source.
09—12
4 capabilities in this set.
Part of 12 available through Honeycomb.
- 09 Capability
Create query specification
The create_query_specification capability creates a new query for a dataset and returns a result ID. It lets your agent build complex queries from plain text instructions.
- 10 Capability
Run query
The run_query capability executes a query specification and returns a result ID for polling. Use it to start the data retrieval process for any custom query.
- 11 Capability
List honeycomb boards
The list_honeycomb_boards capability lists all boards shared with your team. This gives you a quick way to see shared dashboards across the organization.
- 12 Capability
List markers
The list_markers capability lists markers for a dataset. This helps you see all past annotations on a specific timeline.
Set up in minutes
One URL. Then ask Honeycomb to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Honeycomb from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Honeycomb, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Honeycomb for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Honeycomb URL.
- Step 03
Save and start
Save the connection and enable Honeycomb in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"honeycomb": {
"url": "https://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Honeycomb
Open Agent mode in chat and ask: "Using Honeycomb, help me...". 12 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"honeycomb": {
"url": "https://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Honeycomb
Ask Copilot: "Using Honeycomb, help me...". 12 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"honeycomb": {
"url": "https://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Honeycomb
Open Cascade and ask: "Using Honeycomb, help me...". 12 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"honeycomb": {
"url": "https://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Honeycomb
Ask Cline: "Using Honeycomb, help me...". 12 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add honeycomb --transport http "https://edge.vinkius.com/vk_preview_ezx3V1wqKIj03Mpp0VSR1HqDgg5PggVT54nkjF06/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Honeycomb
Ask Claude: "Using Honeycomb, show me...". 12 tools are ready
Where the request belongs
Work Honeycomb can move forward.
SREs and DevOps engineers who are tired of clicking through dashboards at 2am to find a needle in a haystack. It's for the engineer who needs to query high-cardinality data without learning a new syntax every time they have to troubleshoot a production issue.
SRE
Responds to production incidents by asking the agent to find the root cause in the logs.
Software Engineer
Checks the performance of a new feature deployment by pulling specific dataset trends.
Platform Lead
Monitors team board activity and dataset usage across the whole organization.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Manage logs and observability data via Axiom. ingest data, run APL queries, and manage datasets or monitors directly from any AI agent.
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Monitor and manage your Dynatrace environment. query metrics, track problems, manage entities, and automate observability workflows directly from your AI agent.
AppDynamics (Application Performance Monitor API)
Monitor application performance, business transactions, and infrastructure health rules directly from your AI agent.
HyperDX (Open Source Observability)
Monitor logs, events, and alerts via HyperDX. search logs, manage alert rules, and inspect dashboards directly from your AI agent.
Prometheus
Monitor your infrastructure with Prometheus. run PromQL queries, analyze metrics, and manage time-series data directly from your AI agent.
Grafana
Manage observability via Grafana. search and inspect dashboards, monitor alerts, and handle data sources directly from any AI agent.
Bring your own AI
Change the model, client or framework. Keep Honeycomb connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Honeycomb.
The practical details behind the request, access and result.
Can the Honeycomb MCP help me during an outage?
Yes, it lets you query telemetry data instantly using natural language. This helps you find the root cause of issues much faster than manual querying.
How do I use Honeycomb MCP to see my datasets?
You can simply ask your agent to list all the datasets in your team. It will pull the list of available sources directly from your account.
Does Honeycomb MCP support creating markers?
Yes, it handles markers for things like deployments, outages, and maintenance windows. This helps you add context to your timeline data automatically.
Can I see my team's boards with Honeycomb MCP?
Yes, it can list all the boards shared with your team. This gives you a quick way to see your team's dashboards without leaving your current workspace.
What's the benefit of Honeycomb MCP for SREs?
It helps you get answers faster during a crisis. Instead of writing complex DSLs, you can just ask your agent to find the data you need.
How do I get query results from Honeycomb MCP?
The agent runs the query for you and then pulls the results directly into the chat. You don't have to switch tabs to see the data.
How do I find my Honeycomb API Key?
Log in to Honeycomb, go to Team Settings, and navigate to the API Keys section. You will be able to generate and copy your Team API Key from there. Ensure you also note your account's region.
Which region should I select?
If your browser URL starts with ui.eu1.honeycomb.io, select EU. Otherwise, select US. Using the correct region is required for the integration to connect to the right API cluster.
Can I run a query and get the data back?
Yes! Use the run_query capability with a valid query ID. It will return a result ID, which you can then pass to the get_query_result capability once the analysis is complete.
Is the integration secure for telemetry data?
Absolutely. The integration uses official Honeycomb Team API keys over HTTPS. Your credentials and queried data are encrypted and stored securely within the Vinkius Cloud infrastructure.
One connection away
Give your agent a direct line to Honeycomb.
Connect Honeycomb once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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