"How to interact with an Azure DevOps repository" matching MCP servers:

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Enables AI agents to search, read, and traverse a local knowledge base of Markdown files using full-text search and relationship graph, reducing token usage.

Enables AI assistants to search and read Azure documentation using full-text search and section filtering, with content retrieval from Microsoft's official Azure docs repository.

Enables querying Azure Application Insights logs by order number through natural language. Provides secure access to Azure Monitor logs with comprehensive error handling and rate limiting.

Enables natural language exploration of Azure environments by generating and executing KQL queries against Azure Resource Graph. Supports multi-tenant configurations, subscription scoping, and provides direct access to Azure resource information through conversational interactions.

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Enables AI assistants to search and filter Azure platform updates, including previews, general availability, and retirements, through natural language queries.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

A Model Context Protocol server for querying and analyzing Azure resources at scale using Azure Resource Graph, enabling AI assistants to explore and monitor Azure infrastructure.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables AI assistants to search and retrieve Azure service updates, retirements, and feature announcements using natural language queries with fast local caching.

Enables Claude to search and retrieve documents from Azure AI Search indexes with intelligent summarization and analysis using LangGraph workflows and optional Google Gemini integration.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Enables querying Azure retail pricing information, comparing costs across regions and SKUs, estimating usage-based expenses, and discovering Azure services with savings plan information through the Azure Retail Prices API.

Enables Claude Desktop to search private documents using Azure AI Search and perform web searches with Bing, providing AI-enhanced results with source citations through Azure AI Agent Service or direct Azure AI Search integration.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.

Enables Claude to translate natural-language business questions into safe, read-only SQL queries by exposing tools for listing tables, inspecting schemas, and executing row-capped SELECT statements against PostgreSQL.

This read-only MCP Server allows you to connect to Azure Synapse data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).