"facebook ads" matching MCP servers:

MCP Server to interact with Amazon Ads

Provides a read-only MCP interface for Azure Data Factory monitoring and root-cause analysis, with a health check for MCP clients.

Enables MCP clients to directly access Google Analytics 4 data, including property metadata, custom dimensions and metrics, reports, real-time reporting, annotations, and Google Ads links.

Exposes SAP BW/4HANA ADT operations as MCP tools for LLM clients, with a local-file buffering layer to handle large XML payloads and table data efficiently.

Enables Meta Ads account, campaign, ad set, creative, audience, and budget management alongside deterministic marketing growth analytics such as ROAS, CPA, CTR, anomaly detection, cohort retention, and evidence packets. Supports stdio and Streamable HTTP transports with local OAuth or bearer-token authentication.

A local MCP server that unifies advertising campaigns, spend, and analytics from platforms such as Google Ads, Yandex Direct, Telegram Ads, and Microsoft Advertising into one interface for an AI agent, storing data locally in SQLite with explicit confirmation for external actions.

Enables interaction with Azure Data Factory instances, allowing users to list, read, create, update, and trigger pipelines, datasets, linked services, and runs through natural language.

Connect AI assistants to live Meta Ads, GA4, and Google Search Console data. 100% local, credentials machine-locked and encrypted. Supports Claude Desktop, Cursor, Windsurf, Cline, and more.

Enables Claude to fetch and analyze Meta ad accounts, campaigns, ad sets, ads, and performance insights via the Meta Marketing API.

Aggregates job listings from multiple ATS and job board APIs via MCP, enabling unified search and retrieval in a structured format without HTML parsing.

Enables AI agents and terminal users to query LinkedIn Ads (Marketing API) data locally with their own token, covering ad accounts, campaigns, campaign groups, performance metrics, demographic breakdowns, creatives, lead form counts, and campaign targeting. All operations are read-only GET requests, so nothing can be created, edited, paused, or deleted, and lead response details are never fetched.

Enables AI assistants to query unified commerce data from Amazon, Google Ads, GA4, and other selling systems using read-only SQL tools, with managed sync, freshness, and schema discovery.

Enables Claude, Cursor, VS Code, ChatGPT and other MCP clients to analyze Google Search Console, Google Ads and AdSense data through 57 read-only tools covering search performance, indexing, wasted ad spend, quality scores, earnings and combined paid-vs-organic insights. Runs as a thin local client against a hosted backend, so no Google Cloud project, OAuth client or developer token is needed.

Enables MCP clients to delegate analytics questions, sample-size calculation, knowledge retrieval, and metric listing to a deterministic statistical engine over stdio JSON-RPC.

An MCP server that exposes Azure Data Factory operations as tools any LLM can call — trigger pipelines, monitor runs, inspect datasets, and get factory health summaries through natural language.

Databox MCP enables you to query live business metrics from 100+ data sources through AI. Ask natural language questions about marketing performance, sales data, analytics, and financial metrics to get instant insights without switching dashboards. Connect platforms like Google Ads, Salesforce, Shopify, Google Analytics, and more.

Enables AI agents to fetch Xiaohongshu advertising data from Chengfeng, Juguang, and Dandelion platforms via MCP, and supports syncing daily ad reports to Feishu.

Unifies Amazon SP-API and Ads API into 20 MCP tools for orders, inventory, reports, feeds, and advertising, handling auth, throttling, and PII compliance automatically.

Analyse your LinkedIn Ads performance. Compare to benchmarks and get optimisation recommendations.

Enables read-only monitoring and root-cause analysis of Azure Data Factory resources through MCP, allowing users to inspect factories, pipelines, and pipeline runs and diagnose failures via natural language.