"A MongoDB MCP that interacts with MongoDB servers" matching MCP servers:

Enables interaction with MongoDB databases through MCP, supporting database queries, resource reading, and multi-collection operations including aggregation pipelines and lookups.

A powerful Model Context Protocol (MCP) server implementation that provides standardized interaction with MongoDB databases, supporting complete CRUD operations, async patterns, and real-time updates via SSE.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

基于Model Context Protocol (MCP) 的A股实时行情查询服务器，支持查询A股实时价格、历史K线数据、财务信息及市场概况。

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.

An auto-generated Multi-Agent Conversation Protocol server that enables interaction with professional golf data through the SportsData.io Golf v2 API.

Enables Claude to diagnose and fix Azure Data Factory pipeline failures with automated rollback.

An MCP Server that enables interaction with Google's Data Labeling API, allowing users to manage datasets, annotations, and labeling tasks through natural language commands.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Enables querying and mutating data across multiple sources (CSV, Google Sheets, SQLite, PostgreSQL, MySQL, MongoDB, Oracle) through a dynamic GraphQL API, with flexible filtering, batching, persisted queries, and dynamic source switching.

A local MCP server implementation that interacts with DuckDB and MotherDuck databases, providing SQL analytics capabilities to AI Assistants and IDEs.

Celp-MCP enables natural-language analytics over SQL, MongoDB, and Databricks warehouses through MCP-compatible clients, converting questions into multi-step database plans and returning markdown reports.

It interacts with the Kaggle API to provide tools for searching and downloading datasets, and a prompt for generating EDA notebooks.

MCP server that interfaces with the Adjust API, allowing you to query mobile analytics reports, metrics, and performance data using natural language from any MCP client like Cursor or Claude Desktop.

Provides an instant MongoDB MCP server that can be used from any AI agent without local installation.

MCP server with 32 tools for ETL ingestion, AI-generated data quality rules, AI transformations, vector search, and natural-language SQL. Works across Postgres, MongoDB, Kafka, S3/MinIO, HashiCorp Vault, and five vector stores (Qdrant, Weaviate, Milvus, Chroma, pgvector).

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Enables interaction with the Unstructured API to manage data workflows, including creating and managing source connectors (S3, Azure, Google Drive, etc.), destination connectors (Weaviate, Pinecone, MongoDB, etc.), and workflows for document processing and data pipelines.

A universal database adapter that enables read-only queries across PostgreSQL, Supabase, and MongoDB databases via the Model Context Protocol.