"OpsGenie AI - Product Requirements Document (PRD) for AI-Powered Incident Management Platform" matching MCP servers:

Enables secure execution of Python code, SQL queries, and metric fetching through MCP with ephemeral Docker sandboxing.

Enables AI assistants to securely triage SuperOffice CRM support cases by retrieving tickets, running database diagnostics, searching knowledge bases, and orchestrating cross-system incident investigations.

Enables chat, document search (RAG), and a declarative SQL tool builder over MCP so any client can use these capabilities.

Role-aware MCP server over real HPC and cloud log corpora (BGL, OpenStack, Zookeeper) in SereneDB, where every answer cites the exact SQL that ran, backed by a tamper-evident, hash-chained evidence ledger.

A Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.

Enables MCP clients to retrieve relevant memories and save confirmed durable facts through authenticated access backed by PostgreSQL provenance and Qdrant semantic search.

Enables AI-powered interaction with Metabase instances and PostgreSQL databases through natural language. Creates models, SQL queries, metrics, and dashboards using both Metabase API and direct database connections.

Enables a unified AI assistant that combines document retrieval (RAG), database queries via MCP tools, and web search, allowing users to ask complex questions and receive answers from multiple enterprise sources.

Enables governed interaction with synthetic people data through MCP tools, providing per-caller scoped access, semantic-layer metrics, and read-only SQL with authorization checks.

Enables natural language data queries with statistical rigor and a semantic layer, supporting 23+ analytical tools for product analytics.

Enables AI agents to interact with heterogeneous databases (MySQL, MongoDB, BigQuery) through MCP tools, allowing natural language queries and database operations.

A comprehensive Model Context Protocol (MCP) server for product inventory management with PostgreSQL database backend, enabling natural language queries for product information across multiple AI platforms.

Universal database copilot for diagnostics, operations, and performance analysis via MCP and CLI.

Provides tools for managing a product catalog, including functions to list, add, and retrieve product statistics. It enables AI agents to perform inventory operations and data analysis through a standardized interface.

Lets AI agents and developers inspect and query local MySQL, Redis, and MongoDB instances over STDIO or authenticated loopback HTTP, with read-only defaults and allowlisted non-production writes that require explicit opt-in. Production connections always reject writes, and database-enforced read-only accounts are recommended.

A local document evidence layer for MCP clients that ingests documents (PDF, Office, images) with optional OCR, indexes them in SQLite FTS, and provides retrieval tools with source coordinates.

Enables CRUD operations and search on an Excel-backed product catalog, allowing users to list, search, add, update, and delete products.

Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

A production-style MCP server exposing six business tools (web search, database, CRM, email, calendar, analytics) to AI clients via a secure, authenticated interface, with mock mode and a reference agent client.

Manages Supabase projects, databases, edge functions, secrets, and branches across organizations using the Supabase Management API with 24 tools.

Enables an AI assistant to query existing business systems through narrow typed tools, stage and confirm gated writes, and verify stated figures against source data with freshness checks.

Enables read- or write-scoped access to synthetic enterprise orders, inventory, support tickets, and metrics via schema-validated JSON-RPC tools over stdio and HTTP, with permission allow-lists and audit logging. It also exposes enterprise resources and prompt templates for grounded, cited, multi-step assistant workflows.

Sql Builder AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Provides specialized tools for portfolio health analysis, rebalance simulations, and trade execution via a single interface powered by MongoDB. It enables AI agents to manage investment portfolios while adhering to organizational governing rules, clearance guards, and rate limits.

A full-feature MCP server that serves as a product-development copilot, providing RAG search, SQL queries, and inline chart visualizations from seeded product data, with per-user identity and its own OAuth login.

Enables agents to explore a project's captured events and properties, then run trend, funnel and retention analyses and create or list saved insights. Tools are model-oriented, returning trimmed, budgeted results and actionable errors, with the project resolved from the API key or bearer token rather than passed as an argument.

Enables querying a PostgreSQL database using natural language by retrieving context from Azure AI Search and generating SQL with Azure OpenAI, with validation and optional execution.

Enables AI agents to interactively interrogate database schema metadata using SchemaCrawler.

Provides tools to authenticate, search, and manage sessions within WingArc's iA Document Management System. It enables users to perform free word document searches and manage security tokens through the Model Context Protocol.