"Qubes OS" matching MCP servers:

Enables AI agents to query, send, and manage data from Claro Gerencial SOAP webservices, including listing entities, fetching records, generating FTP files, and submitting XML imports.

Enables AI assistants such as Claude to read fields, boundaries, field operations, equipment, machine health, products, operators, guidance lines, and work plans from a John Deere Operations Center account on the user's own computer. It is read-only and cannot change anything in Operations Center.

Enables MCP-compatible AI assistants to analyze restaurant menu economics from CSV data, including food-cost percentages, contribution margins, gross sales, ingredient costs, and item rankings. It can flag loss-making items and periods with no sales.

An npx-compatible port of @Axiom's mcp-server-axiom

Enables AI agents to interact with Microsoft Fabric by exposing tools for managing workspaces, notebooks, SQL queries, pipelines, and Livy Spark sessions. It provides a comprehensive set of operations for data engineering and analytics tasks using standard Azure authentication.

Enables restaurant management through natural language, allowing import of Toast CSV data, labor/sales analysis, tip pool calculations, task management, and note-taking.

Read-only MCP server for self-hosted Airbyte OSS 1.6.x, enabling monitoring of connections, jobs, and health via public and internal APIs. Optionally supports triggering syncs and canceling jobs.

A read-only MCP server that exposes dbt project artifacts and data quality result tables (BigQuery/Postgres) to LLM clients, enabling deep introspection, run-history analysis, source freshness, test coverage, and lineage walks.

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

Enables tracking of Tarkov PvE progress, item needs, stash contents, and task/route verdicts via an MCP server.

A Model Context Protocol (MCP) server that integrates the FAIM time series forecasting SDK with any MCP-compatible AI assistant, enabling AI-powered forecasting capabilities.

Enables AI agents to list metrics and dimensions, inspect definitions, and run governed metric queries against Apache Iceberg tables through a semantic layer, without writing SQL or accessing raw rows or columns outside their role.

Enables AI assistants to read and search Kafka messages through the Redpanda Console HTTP API, including topic listing, message fetching by offset or time, and substring search, without direct Kafka broker access.

Airflow MCP server — read DAGs, runs, task instances, log tails; trigger and clear (write-gated).

An AI-powered treasury management MCP server that enables users to perform commercial banking analysis, including cash flow forecasting, idle cash detection, and debt covenant monitoring. It provides tools to surface financial insights and optimize working capital through automated processing of bank and transaction data.

Provides access to Chinese A-share market financial data, including historical K-line, real-time quotes, financial statements, shareholder information, and technical indicators, via MCP protocol.

Connects Claude Desktop to Garmin Connect, enabling natural language queries of fitness activity data, health metrics, sleep analysis, workout management, and device information with 94 available tools.

Material, cell, pack, and supply-chain management with real-time

Exposes Microsoft Fabric operations as MCP tools, with 105 tools across 17 domains including lakehouses, warehouses, notebooks, pipelines, and real-time analytics, handling long-running operations and supporting multiple authentication modes.

A Python MCP server that lets you manage Microsoft Fabric through natural language in Claude Code or Claude Desktop, with 77+ tools covering workspaces, lakehouses, warehouses, SQL, DAX, semantic models, notebooks, pipelines, OneLake, and Microsoft Graph.

Enables Claude to query and manipulate GRID spreadsheets via the GRID API using natural language.

Enables an AI assistant to read, validate, and maintain a local wealth document, list holdings, record dated valuations, compute net worth by currency, and import spreadsheet data over stdio without network access.

Enables exposing third-party data sources as Model Context Protocol servers with shared HTTP, rate limits, retries, caching, validation, and observability through thin per-source adapters.

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 agents to compare two tables across the same or different databases and report what changed, which columns changed, and where changes concentrate, plus source/table discovery and schema description. Runs four read-only tools that take source names rather than connection strings, returning a stable JSON contract with a risk verdict.

Enables AI agents to ingest and link datasets, plan and render interactive D3.js visualizations and dashboards, validate and refine outputs, and export standalone HTML, SVG, PNG, PDF, JSON, or CSV artifacts from natural-language requests.

Enables orchestrating data quality checks, transformation, and deduplication pipelines via an MCP interface. Offers tools for listing pipeline stages, validating wiring, running the full check-transform-match pipeline, and explaining configurations.

Enables agents to run zero-config entity resolution on messy records from CSVs, tables or databases, automatically choosing match rules and clustering duplicates into stable entities with per-field provenance. Exposes the resulting identity layer through dozens of tools for deduping, merging/splitting records, auditing changes, and answering Customer 360 questions.

A FastMCP server that exposes Informatica IDMC Data Integration APIs as MCP tools, allowing AI agents to query, run, and monitor CDI mappings through natural language.

Answers whether a route ran late and by how much, with drill-down into individual trip delays and an audit trail of data-quality exclusions and duplicate resolutions.