Cover image
Try Now
2025-04-01

MCP Server to interact with the Demand API

3 years

Works with Finder

10

Github Watches

0

Github Forks

0

Github Stars

🏆 Audiense Demand MCP Server

smithery badge

This server, based on the Model Context Protocol (MCP), allows Claude or any other MCP-compatible client to interact with your Audiense Demand account. It provides tools to create and analyze demand reports, track entity performance, and gain insights across different channels and countries.

This MCP server is designed to work with the Audiense Demand API and requires an Audiense account authorized to use Audiense Demand.

We provide two different guides based on your background and needs:

🌟 For Business Users and Non-Developers

If you're primarily interested in using the Audiense Demand tools with Claude or another "MCP compatible" tool and don't need to understand the technical details, follow our User Guide. This guide will help you:

  • Install the necessary software quickly
  • Set up Claude Desktop
  • Start creating and analyzing demand reports
  • Troubleshoot common issues

🛠️ For Developers and Technical Users

If you're a developer, want to contribute, or need to understand the technical implementation, follow our Developer Guide. This guide covers:

  • Detailed installation steps
  • Project architecture
  • Development setup
  • Advanced configuration
  • API documentation
  • Contributing guidelines

🛠️ Available Tools

📌 create-demand-report

Description: Creates a new demand report for specified entities.

  • Parameters:

    • title (string): Title of the demand report
    • entitiesReferences (array of strings): Array of entity names for the report
    • userEmail (string): Email of the user creating the report
  • Response:

    • Report creation details in JSON format

📌 get-demand-reports

Description: Retrieves the list of demand reports owned by the authenticated user.

  • Parameters:

    • paginationStart (number, optional): Pagination start index
    • paginationEnd (number, optional): Pagination end index
  • Response:

    • List of reports in JSON format

📌 get-demand-report-info

Description: Fetches detailed information about a specific demand report.

  • Parameters:

    • reportId (string): The ID of the report to get information for
  • Response:

    • Full report details in JSON format

📌 get-demand-report-summary-by-channels

Description: Gets a summary of the report broken down by channels.

  • Parameters:

    • reportId (string): The ID of the report to get the summary for
    • country (string, default: "Weighted-Total"): The country to filter by
    • offset (number, default: 0): Pagination offset
    • entityNames (array of strings, optional): Optional array of entity names to filter by
  • Response:

    • Channel-wise summary data in JSON format

📌 get-demand-report-summary-by-countries

Description: Gets a summary of the report broken down by countries.

  • Parameters:

    • reportId (string): The ID of the report to get the summary for
    • platform (string, default: "all_platforms"): Platform name to analyze
    • countries (array of strings): Array of country codes to analyze
    • offset (number, optional): Pagination offset
    • entityNames (array of strings, optional): Optional array of entity names to filter by
  • Response:

    • Country-wise summary data in JSON format

📌 get-youtube-search-volume-summary

Description: Gets YouTube search volume summary for entities in a report.

  • Parameters:

    • reportId (string): The ID of the report to get the summary for
    • country (string, default: "Global"): Country code to analyze
    • entityNames (array of strings, optional): Optional array of entity names to filter by
  • Response:

    • YouTube search volume data in JSON format

📌 get-google-search-volume-summary

Description: Gets Google search volume summary for entities in a report.

  • Parameters:

    • reportId (string): The ID of the report to get the summary for
    • country (string, default: "Global"): Country code to analyze
    • entityNames (array of strings, optional): Optional array of entity names to filter by
  • Response:

    • Google search volume data in JSON format

📌 check-entities

Description: Checks if entities exist and gets their details.

  • Parameters:

    • entities (array of strings): Array of entity names to check
  • Response:

    • Entity status information in JSON format

📄 License

This project is licensed under the Apache 2.0 License. See the LICENSE file for more details.

相关推荐

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Yusuf Emre Yeşilyurt
  • I find academic articles and books for research and literature reviews.

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Carlos Ferrin
  • Encuentra películas y series en plataformas de streaming.

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://zenepic.net
  • Embark on a thrilling diplomatic quest across a galaxy on the brink of war. Navigate complex politics and alien cultures to forge peace and avert catastrophe in this immersive interstellar adventure.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • https://reddgr.com
  • Delivers concise Python code and interprets non-English comments

  • 林乔安妮
  • A fashion stylist GPT offering outfit suggestions for various scenarios.

  • 田中 楓太
  • A virtual science instructor for engaging and informative lessons.

  • 1Panel-dev
  • 💬 MaxKB is a ready-to-use AI chatbot that integrates Retrieval-Augmented Generation (RAG) pipelines, supports robust workflows, and provides advanced MCP tool-use capabilities.

  • Mintplex-Labs
  • The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.

  • ShrimpingIt
  • Micropython I2C-based manipulation of the MCP series GPIO expander, derived from Adafruit_MCP230xx

  • GLips
  • MCP server to provide Figma layout information to AI coding agents like Cursor

  • open-webui
  • User-friendly AI Interface (Supports Ollama, OpenAI API, ...)

    Reviews

    1 (1)
    Avatar
    user_iU7oy5Dk
    2025-04-16

    As a dedicated MCP user, I have found the mcp-audiense-demand by AudienseCo to be incredibly valuable for understanding audience demand and trends. The product is robust, user-friendly, and integrates seamlessly into my workflow. Highly recommended for anyone looking to gain deep market insights! Check it out at https://github.com/AudienseCo/mcp-audiense-demand.