Microsoft Ads is now live on Adsroid MCP. With 37 dedicated Microsoft Advertising tools and more than 220 tools across the Adsroid ecosystem, AI assistants can now access Microsoft Ads performance data alongside Google Ads, Meta Ads, Google Analytics 4, Google Search Console, HubSpot, WordPress, and competitive intelligence.

The result is a more powerful way to analyze advertising performance, uncover optimization opportunities, and connect marketing data across platforms, all through a single MCP endpoint.

One MCP. 220+ Tools. Your Entire Marketing Stack.

Marketing teams increasingly rely on AI assistants to analyze data, identify opportunities, and make better decisions. But there is still a major limitation: marketing data lives across disconnected platforms.

Google Ads has its own reporting environment. Microsoft Advertising has its own API. Meta Ads operates independently. Analytics, CRM, SEO, and website data are scattered across different systems.

Connecting each platform separately creates unnecessary complexity for AI workflows.

Adsroid MCP was built to solve this problem.

Rather than connecting an AI assistant to individual platforms through separate integrations, Adsroid provides a unified Model Context Protocol (MCP) server that exposes more than 220 specialized tools through a single endpoint.

With the latest Microsoft Advertising integration, the ecosystem now brings together:

• Google Ads: Campaign analysis, keyword performance, search terms, budgets, bidding, campaign management, and creation.
• Microsoft Advertising: Advanced campaign, keyword, search term, audience, device, geographic, and conversion analysis.
• Meta Ads: Advertising performance, campaign analysis, creative insights, and campaign management.
• Google Analytics 4: Website performance, traffic acquisition, user behavior, and conversion analysis.
• Google Search Console: Organic search performance, queries, rankings, and visibility.
• HubSpot: CRM and customer relationship data.
• WordPress: Website and content management workflows.
• Adsroid Competitive Intelligence: Competitor advertising intelligence and market monitoring through Ad Radar.

All these capabilities are accessible through the same MCP infrastructure.

Instead of asking AI to analyze isolated reports, marketers can give it access to a much broader view of their marketing operations.

Microsoft Advertising MCP: 37 Tools for Advanced Campaign Analysis

The main objective behind the Microsoft Ads integration was not simply to expose basic campaign statistics.

Microsoft Advertising provides a substantial amount of performance and operational data. We wanted AI assistants to be able to retrieve meaningful information at multiple levels of the advertising account.

The new integration includes 37 dedicated tools covering different dimensions of Microsoft Ads performance.

1. Account and campaign performance analysis

AI assistants can retrieve account-wide performance metrics and compare campaigns across any supported reporting period.

Available metrics include:

• Impressions and clicks
• Advertising spend
• Click-through rate (CTR)
• Average cost per click (CPC)
• Cost per thousand impressions (CPM)
• Conversions and conversion rate
• Conversion value and revenue
• Return on ad spend (ROAS)
• Cost per conversion
• Assisted and view-through conversions
• Impression share and lost impression share
• Click share
• Phone calls and other specialized performance metrics

Reports can be segmented by device, network, match type, conversion goal, and reporting period, including daily, weekly, and monthly aggregation.

This allows AI agents to investigate performance beyond surface-level KPIs.

For example:

“Analyze my Microsoft Advertising account over the last 30 days. Identify campaigns with declining ROAS, increasing CPC, or significant impression share losses. Prioritize the opportunities based on potential business impact.”

2. Keyword and search term intelligence

Understanding the difference between the keywords advertisers target and the actual search queries triggering their ads is essential to optimizing paid search campaigns.

The Microsoft Ads MCP provides access to both keyword-level and search term-level performance.

AI assistants can:

• Retrieve all account keywords.
• Analyze individual keyword performance.
• Compare keyword performance across campaigns.
• Retrieve impressions, clicks, spend, CTR, CPC, and conversions.
• Investigate individual search queries.
• Identify search terms generating unnecessary expenditure.
• Find non-converting queries and potential negative keywords.
• Analyze keyword match types and current maximum CPC bids.
• Retrieve and inspect shared negative keyword lists.

This makes it possible to automate detailed search term audits using natural language.

Example:

“Analyze all Microsoft Ads search terms from the last 30 days. Find queries that generated more than €50 in spend without producing a conversion. Group them by campaign and recommend which ones should become negative keywords.”

AI can also identify new keyword opportunities by analyzing actual search behavior rather than relying exclusively on existing keyword lists.

3. Audience performance and targeting analysis

Microsoft Advertising offers different audience targeting options, including remarketing lists, customer lists, in-market audiences, custom audiences, product audiences, and combined lists.

Adsroid MCP exposes tools to retrieve audience configurations and evaluate their performance.

AI assistants can:

• Discover available audience lists.
• Identify audiences associated with specific campaigns.
• Inspect ad group-level audience associations.
• Retrieve audience performance metrics.
• Compare impressions, clicks, spend, and conversions.
• Identify audiences generating stronger conversion performance.

This creates opportunities to understand which audience segments contribute most to advertising results.

Example:

“Compare the performance of all active Microsoft Ads audiences over the last 60 days. Identify the audiences generating the highest conversion volume and the lowest cost per conversion.”

4. Device and geographic performance

Performance can vary considerably depending on where and how users interact with advertisements.

The integration provides dedicated reporting tools for device and geographic analysis.

Device analysis

Break down campaign performance by:

• Desktop
• Smartphones
• Tablets

Compare impressions, clicks, spend, and conversions to identify differences in acquisition efficiency.

Geographic analysis

Analyze performance by:

• Country
• State or region
• City

AI assistants can identify locations consuming a disproportionate share of advertising budgets, discover high-performing geographic markets, and recommend where campaigns deserve more attention.

Example:

“Compare desktop and mobile performance across all Microsoft Ads campaigns. Identify campaigns where mobile traffic generates significantly more expensive conversions.”

5. Time-based performance analysis

Campaign performance is not necessarily consistent throughout the day or across the week.

Adsroid MCP provides hourly and daily reporting capabilities for Microsoft Advertising campaigns.

This makes it possible to investigate:

• High-performing hours.
• Low-performing time periods.
• Differences between weekdays and weekends.
• Conversion patterns throughout the day.
• Periods with unusually high advertising expenditure.

Example:

“Analyze hourly Microsoft Ads performance over the last 30 days. Identify the hours generating the most conversions and the periods where spend is high but conversion activity is low.”

These insights can help advertisers make more informed decisions about campaign scheduling and budget allocation.

6. Conversion tracking and measurement

Reliable conversion tracking is fundamental to any advertising optimization strategy.

AI assistants can retrieve Microsoft Advertising conversion goal configurations, including:

• Conversion goal names and IDs.
• Goal types and statuses.
• Tracking status.
• Conversion counting settings.
• Conversion windows.
• Revenue configuration.
• UET tag associations.
• Whether conversion goals are excluded from bidding.
• Event and URL-based conversion conditions.

This allows AI to investigate potential measurement problems before making optimization recommendations.

For example:

“Review my Microsoft Advertising conversion goals. Identify active goals that are not recording recent conversions, and highlight any configuration issues that could affect campaign optimization.”

7. Landing page performance

Advertising performance does not stop at the click.

The new integration also exposes landing page performance data, allowing AI assistants to analyze the relationship between ads, destinations, and conversion results.

Available metrics include:

• Impressions.
• Clicks.
• Spend.
• Conversions.
• Conversion rate.
• Average CPC.
• Final landing page URL.
• Associated campaign, ad group, and ad.

This provides a useful foundation for identifying landing pages that receive significant advertising investment but generate comparatively weak conversion results.

Example:

“Identify the Microsoft Ads landing pages receiving the highest spend but generating the lowest conversion rates. Rank them by potential optimization priority.”

8. Ad extensions and asset performance

Ad extensions and responsive search ad assets can have a meaningful impact on advertising performance.

The Microsoft Ads integration provides access to extension configurations and their associated reporting data.

Supported extension types include:

• Sitelinks.
• Callouts.
• Call extensions.
• Image extensions.
• Structured snippets.

AI assistants can inspect extension configurations and evaluate their performance through impressions, clicks, spend, and qualified conversions.

The integration also retrieves Responsive Search Ads asset information, including headlines, descriptions, editorial statuses, pinned positions, and performance ratings such as Low, Good, Best, Learning, and Unrated.

This allows AI agents to identify weaker ad assets and suggest improvements based on available performance signals.

9. Performance Max, experiments, and account change history

The integration also covers more specialized advertising analysis.

Performance Max asset groups

Retrieve asset group performance data, including impressions, clicks, spend, and conversions, to compare results across Performance Max campaigns.

Campaign experiments

Discover Microsoft Advertising experiments and inspect their configurations, including:

• Experiment names and IDs.
• Base and experiment campaign IDs.
• Traffic split percentages.
• Start and end dates.
• Experiment statuses and types.

Change history

Retrieve account change history to understand what happened inside an advertising account.

This includes timestamps, users, affected campaigns and ad groups, modified attributes, change types, previous and new values, and the source of each modification.

This is particularly useful when investigating unexpected performance changes or understanding the impact of previous optimizations.

Beyond Microsoft Ads: Cross-Platform Marketing Intelligence

The real opportunity is not simply having more Microsoft Advertising reporting tools.

It is combining Microsoft Ads data with information from the rest of the marketing stack.

When an AI assistant has access to multiple platforms through Adsroid MCP, it can investigate questions that would otherwise require several dashboards, exports, and manual analysis.

Consider these workflows.

Google Ads vs. Microsoft Ads performance

“Compare Google Ads and Microsoft Ads performance over the last 30 days. Analyze CPC, conversion rate, CPA, and ROAS. Identify which platform delivers the most efficient acquisition and where we should investigate budget allocation opportunities.”

Instead of analyzing two advertising platforms separately, AI can retrieve the relevant data and build a consolidated performance analysis.

Paid search vs. organic search

“Compare the search terms generating conversions in Microsoft Ads and Google Ads with the organic queries reported by Google Search Console. Identify opportunities where we have strong paid performance but limited organic visibility.”

This connects paid search intelligence with SEO opportunities.

Advertising performance vs. website behavior

“Analyze our Microsoft Ads campaigns alongside Google Analytics 4 data. Identify campaigns generating clicks but showing weak engagement or conversion performance on the website.”

This helps move beyond advertising platform metrics to investigate what happens after users arrive on the website.

Advertising vs. CRM performance

“Compare our advertising acquisition data with HubSpot CRM performance. Identify which campaigns generate the highest volume of qualified leads rather than simply the most conversions.”

This is particularly valuable for B2B companies, where a conversion does not necessarily represent a qualified opportunity or a paying customer.

These examples illustrate a fundamental advantage of unified marketing infrastructure: AI can connect signals from different systems to provide more meaningful business insights.

The more relevant context an AI assistant can access, the more useful its analysis becomes.

Why Adsroid MCP Is Different From Other Advertising MCP Servers

Not all MCP integrations provide the same capabilities.

Some expose only a handful of API endpoints. Others focus exclusively on one advertising platform or one specific use case.

Adsroid takes a different approach.

One endpoint instead of multiple integrations

Adsroid MCP provides a single endpoint for all connected platforms.

There is no need to configure an independent MCP server for Google Ads, another for Microsoft Advertising, and another for analytics.

One connection provides access to the available tools across the Adsroid ecosystem.

Depth, not just the number of integrations

Having 220+ tools is not valuable simply because the number is large.

The important question is what those tools actually allow an AI assistant to do.

The Microsoft Ads integration illustrates this philosophy: instead of exposing only basic account and campaign reporting, it provides dedicated capabilities for keywords, search terms, audiences, geographic analysis, device performance, landing pages, conversion goals, ad assets, experiments, and change history.

The objective is to give AI agents the information required to perform meaningful marketing analysis.

Multi-account and multi-project architecture

Adsroid MCP is designed for agencies, consultants, and organizations managing multiple advertising accounts.

Through the same connection, an AI assistant can access different projects and their associated platforms.

This opens the door to cross-client reporting, account comparisons, benchmarking, and consolidated marketing analysis.

For agencies, this means less time switching between accounts and more time analyzing performance.

Business context built into the AI workflow

Access to data is only one part of the equation.

A campaign’s performance should always be evaluated in relation to the business behind it.

Adsroid includes a Business Context layer that allows projects to carry relevant information about their positioning, products, target audiences, unique selling propositions, and business objectives.

This helps AI assistants move beyond generic recommendations.

For example, a campaign with a high CPC is not necessarily underperforming if it generates valuable, high-intent customers.

Understanding the business context helps AI produce more relevant strategic recommendations.

Real-time API access and data privacy

Adsroid MCP is designed around real-time interactions with connected platforms.

When an AI assistant requests information, the MCP server routes the request to the relevant platform API and returns the response.

Adsroid’s MCP architecture is designed not to retain or cache advertising account data at the MCP server level.

This approach provides access to live platform information without requiring a separate reporting database to power every MCP interaction.

Compatible with MCP-enabled AI assistants

Adsroid follows the Model Context Protocol standard, making its tools accessible through compatible AI clients.

Depending on the client and its MCP support, this includes environments such as:

• Claude Desktop.
• Claude Code.
• Cursor.
• Other MCP-compatible AI assistants and development environments.

Developers can also use the Adsroid API to build custom integrations and workflows.

How to Connect Microsoft Ads to Your AI Assistant

Connecting Microsoft Advertising through Adsroid MCP is straightforward.

You do not need to build your own Microsoft Advertising API integration or maintain individual connections for every advertising platform.

The process is designed to be simple:

Step 1 – Connect your advertising accounts

Create an Adsroid account and connect your Microsoft Advertising account through the available integration.

Step 2 – Open your MCP-compatible AI client

Choose the AI assistant or development environment you want to use.

Step 3 – Add the Adsroid MCP endpoint

Use the unified endpoint:

https://mcp.adsroid.com/mcp

Step 4 – Authenticate your connection

Follow the authentication flow using your Adsroid API key.

Step 5 – Start analyzing your marketing data

Ask your AI assistant to investigate campaign performance, compare keywords, analyze audiences, identify optimization opportunities, or combine data across connected platforms.

No separate MCP server is required for each advertising platform.

For detailed instructions, visit the Adsroid MCP documentation.

The Future of Marketing Is Not Another Dashboard. It Is AI That Can Work Across Your Entire Stack.

The way marketers interact with advertising platforms is changing.

For years, managing digital advertising meant navigating dashboards, exporting reports, building spreadsheets, and manually connecting information from different platforms.

AI assistants are changing this workflow.

But an AI model is only as useful as the information and tools it can access.

Giving an AI assistant access to campaign data is a starting point. Giving it access to advertising performance, SEO, website analytics, CRM information, and competitive intelligence through one unified infrastructure is a much bigger step.

With Microsoft Advertising now integrated and more than 220 tools available across the Adsroid MCP ecosystem, we are continuing to build toward that vision.

One endpoint. Multiple platforms. Hundreds of specialized tools. One AI-powered marketing ecosystem.

Explore Adsroid MCP and connect your marketing stack to AI.

Discover Adsroid MCP

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Frequently Asked Questions

What is Adsroid MCP?

Adsroid MCP is a unified Model Context Protocol server that connects AI assistants to advertising and marketing platforms through a single endpoint. It provides access to more than 220 specialized tools covering Google Ads, Meta Ads, Microsoft Advertising, Google Analytics 4, Google Search Console, HubSpot, WordPress, and competitive intelligence capabilities.

Does Adsroid MCP support Microsoft Advertising?

Yes. Microsoft Advertising is now integrated into Adsroid MCP with 37 dedicated tools for advanced advertising analysis, including campaign performance, keywords, search terms, audiences, devices, geographic data, conversion goals, landing pages, ad extensions, Performance Max asset groups, experiments, and change history.

Can AI analyze Microsoft Ads campaigns?

Yes. AI assistants connected to Adsroid MCP can retrieve Microsoft Advertising data and analyze campaigns, ad groups, keywords, search terms, audiences, devices, locations, conversions, and other performance dimensions. They can identify trends, compare results, and generate data-driven optimization recommendations.

Can I compare Google Ads and Microsoft Ads using AI?

Yes. Because both platforms are available through the same Adsroid MCP endpoint, an AI assistant can retrieve data from both platforms and compare their performance within the same conversation. This includes spend, CPC, CTR, conversions, CPA, and ROAS, subject to the metrics available from each platform.

How many tools does Adsroid MCP provide?

Adsroid MCP provides more than 220 specialized tools across its connected advertising and marketing ecosystem. This includes 37 dedicated Microsoft Advertising tools, alongside tools for Google Ads, Meta Ads, analytics, SEO, CRM, website management, and competitive intelligence.

Does Adsroid MCP only provide read-only access?

No. The broader Adsroid MCP ecosystem includes both analytical and operational capabilities, depending on the connected platform. AI assistants can analyze data and, where supported, create campaigns, manage advertising structures, adjust settings, and perform other operations. The current Microsoft Advertising integration focuses on the 37 analytical and data-retrieval capabilities described in this announcement.

Which AI assistants are compatible with Adsroid MCP?

Adsroid MCP follows the Model Context Protocol standard and is designed to work with MCP-compatible clients, including Claude Desktop, Claude Code, Cursor, and other supported AI environments.

Do I need a separate MCP integration for every advertising platform?

No. Adsroid MCP provides a unified endpoint for its connected platforms. You configure the Adsroid MCP connection once and access the available tools across your connected projects and accounts.

Is advertising data stored by Adsroid MCP?

The MCP infrastructure is designed to retrieve platform information in real time without retaining or caching advertising account data at the MCP server level. Authentication and account access are handled through the Adsroid connection architecture.

Who should use Adsroid MCP?

Adsroid MCP is particularly useful for digital marketing agencies, PPC specialists, performance marketers, marketing consultants, developers, and organizations managing multiple advertising platforms or client accounts. It helps reduce integration complexity and enables AI-driven marketing analysis across different systems.