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The Nebuly MCP Server lets AI assistants query Nebuly data through the Model Context Protocol. Use it to ask questions about interactions, conversations and aggregated data, to build and update reports and charts, or to export interaction CSV files without leaving your assistant.
The Nebuly MCP Server is currently in beta and available to all SaaS users and self-hosted customers.SaaS users can connect directly using https://mcp.nebuly.com/mcp.Self-hosted customers should use the URL provided by the Nebuly team.

Prerequisites

Before you configure the integration, make sure you have:
  • A Nebuly account with MCP access (all SaaS users, or a self-hosted environment with MCP beta enabled).
  • Your Nebuly MCP server URL, shown below as <NEBULY_MCP_URL>. SaaS users should use https://mcp.nebuly.com/mcp.
  • One of the supported MCP clients: Claude Desktop, Claude Code, or Cursor.

Configure your MCP client

Detailed instructions for adding the Nebuly MCP server to Claude Desktop can be found in the Claude Desktop documentation.This typically requires organization-level configuration, so please reach out to your Claude administrator if you don’t have access to the settings described in the documentation.

MCP Overview

Example usage

After defining a project to work with, your assistant can answer a wide variety of questions about your Nebuly data.
Hey assistant, I want to use Nebuly MCP server!
We will work on the Production project, London timezone.
Not all agents have access to your current position, to ensure the same results shown in the Nebuly UI provide your location/timezone in the conversation.
Try asking your MCP-enabled assistant:
  • “List the Nebuly projects I can access.”
  • “Show me the top 10 topics by interaction volume over the last 30 days.”
  • “Show me a chart of negative-sentiment interactions by topic and user intent for the last two weeks.”
  • “Show daily interaction volume and error-rate trends for the last quarter.”
  • “Which topics have the highest average latency this month?”
  • “List the reports in the project.”
  • “Create a report called ‘Monthly Quality’ and add a line chart of daily interaction volume for the last 30 days.”
  • “Add a pie chart of interactions by topic for last month to my ‘Monthly Quality’ report.”
  • “Export January interactions with timestamp, user, input, output, topic, sentiment, and cost.”

Available tools

Interactions and conversations

  • list_projects: List the Nebuly projects your assistant can access.
  • get_interactions: Query interactions in a project with filters. Results will be paginated and limited, this tool is designed for browsing and inspecting small sets of interactions, not for bulk data retrieval.
  • get_interaction_details: Retrieve the full record for a single interaction, based on an interaction ID.
  • get_conversation_detail: Fetch the full conversation history based on a conversation ID.

Analytics

  • get_interaction_aggregates: Group interactions by one dimension, such as topic, sentiment, user intent, language, feedback, risk type, or custom fields.
  • get_interaction_multi_aggregates: Break down interactions across multiple dimensions, such as topic by sentiment or intent by feedback.
  • get_interaction_time_series: Build trends over time with minute, hour, day, week, month, or year buckets.
  • get_interaction_query_options: Used by agents to discover how to filter and group interactions.
The analytics tool gets best result when used from assistants that can handle tabular data and charts, such as Claude Desktop or Cursor.

Reports and charts

  • list_reports: List the reports in a project.
  • get_report: Fetch a single report with its full configuration and charts.
  • create_report: Create a new report in a project.
  • update_report: Update an existing report’s metadata or favorite status.
  • create_analytics_chart: Add an analytics chart to a report.
  • update_analytics_chart: Update an existing analytics chart.
  • create_table_chart: Add a table chart to a report.
  • update_table_chart: Update an existing table chart.
  • get_chart_builder_options: Used by agents to discover how to build charts.
  • get_filter_values: Used by agents to discover the distinct selectable values for a given chart filter.
  • get_filter_definition: Used by agents to discover specific details about a chart filter.
Currently the MCP server supports the following chart types:
  • Time series
  • Horizontal bar chart
  • Stacked time series
  • Metric
  • Time series distribution
  • Scatter plot
  • Pie
  • Table

Exports

  • get_interactions_csv: Start an async CSV export for a filtered set of interactions. By default the export will include timestamp, input and output. You can ask your assistant to include additional fields such as user, topic, sentiment or cost.
  • get_csv_export_status: The agent will use this to check the status of a running export job. Returns pending, running, completed, or failed with a progress percentage.
  • prepare_csv_download: The agent will use this to obtain a time-limited download URL. The URL expires after 5 minutes.