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Honeycomb MCP Server

honeycomb.io
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Automate observability via Honeycomb — manage datasets, queries, and markers directly from any AI agent.

Vinkius AI Gateway prend en charge le streamable HTTP et le SSE.

Honeycomb

Fonctionne avec tous les agents IA que vous utilisez déjà

…et tout client compatible MCP

CursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWSCursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWS

Honeycomb MCP Server : voyez votre AI Agent en action

AI Agent→Vinkius→Honeycomb
You

Vinkius AI Gateway
GDPR·High Security·Kill Switch·Ultra-Low Latency·Plug and Play

Capacités intégrées (12)

create_marker

Pass details as a JSON string in "body_json" (requires message). Use "__all__" for team-wide markers. Create a new marker (e.g., deploy, maintenance) on a dataset timeline

create_query_specification

Pass the specification as a JSON string in "query_json". Returns a query ID for execution. Create a new query specification for a dataset

get_dataset_details

Get metadata for a specific dataset

get_query_result

Retrieve the results of an executed query

get_team_details

Retrieve information about the Honeycomb team

list_dataset_columns

List all columns (fields) defined in a specific dataset

list_datasets

Use this to find the "slug" required for markers and queries. List all datasets in your Honeycomb team

list_honeycomb_boards

List all boards (dashboards) shared with the team

list_markers

List markers (annotations) for a dataset

list_queries

List query specifications for a specific dataset

list_triggers

List triggers (alerts) defined for a dataset

run_query

Poll for results using "get_query_result" with the returned result ID. Execute a query specification and return a result ID

Ce que ce connecteur débloque

Connect your Honeycomb.io observability platform to any AI agent and take full control of your telemetry data, query specifications, and incident markers through natural conversation.

What you can do

  • Dataset Oversight — List all event sources, retrieve detailed metadata, and monitor last access times for your datasets.
  • Query Management — Define new query specifications and execute them to retrieve granular performance insights.
  • Marker Automation — Create timeline annotations (e.g., for deployments or outages) to contextualize your data visualization.
  • Schema Insights — List and inspect columns within specific datasets to understand your event structure.
  • Team Collaboration — Access shared boards and retrieve information about your Honeycomb team configuration.
  • Incident Analysis — Use AI to run complex queries and retrieve results for rapid troubleshooting and RCA.

How it works

1. Subscribe to this server
2. Enter your Honeycomb API Key and select your Region (US or EU)
3. Start querying your telemetry from Claude, Cursor, or any MCP-compatible client

No more manual configuration of complex query DSLs for simple status checks. Your AI assistant acts as a dedicated Observability Engineer or SRE Analyst.

Who is this for?

  • SREs & DevOps — instantly retrieve query results and create markers during incident response.
  • Software Engineers — monitor the performance of new deployments by inspecting specific dataset trends.
  • Platform Leads — maintain a real-time overview of dataset usage and board sharing across the organization.

Questions fréquemment posées

Donnez à vos agents IA la puissance de Honeycomb

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DÉTAILS
CatégorieBrain Trust
Mots-clés
telemetryhigh-cardinalityincident-responsedata-queryingreal-time-insights
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