Excel MCP Server enables AI agents and applications to create, read, and modify Excel workbooks without relying on Microsoft Excel. It provides comprehensive Excel operations such as editing sheets, managing data, generating charts, and working with pivot tables through various transport protocols including stdio and HTTP. The server supports robust data validation, advanced formatting, and seamless integration as both a local tool and remote service. Configuration options for file management and port settings allow for flexible deployment.

• ⭐ 2,795
• MCP
• haris-musa/excel-mcp-server

Alkemi MCP Server provides a STDIO wrapper for connecting Alkemi data sources—including Snowflake, Google BigQuery, and Databricks—with MCP Clients using the Model Context Protocol. It facilitates context sharing, database metadata management, and query generation through a standardized protocol endpoint. Shared MCP Servers allow teams to maintain consistent, high-quality data querying capabilities without needing to replicate schemas or query knowledge for each agent. Out-of-the-box integration with Claude Desktop and robust debugging tools are also included.

• ⭐ 2
• MCP
• alkemi-ai/alkemi-mcp

MCP GitLab Jira Server acts as a bridge, enabling AI agents to interact programmatically with GitLab and Jira instances via the Model Context Protocol. It provides a standardized server interface for operations on projects, merge requests, pipelines, branches, issues, releases, and users in GitLab, as well as tickets and project management features in Jira. The server can be run as a CLI tool or in a Docker container, making it compatible with tools like gemini-cli. Configuration via environment variables allows secure authentication and flexible deployment.

• ⭐ 6
• MCP
• HainanZhao/mcp-gitlab-jira

Databricks Genie MCP Server enables interaction between large language models and the Databricks Genie API using the Model Context Protocol. It allows users to ask natural language questions, start and manage conversations, and run SQL queries in Genie spaces. The tool provides structured results, supports follow-up queries, and facilitates connection through both standard and Docker-based setups. Designed for use with Claude Desktop, it streamlines conversational analytics within Databricks workspaces.

• ⭐ 12
• MCP
• yashshingvi/databricks-genie-MCP

CrateDocs MCP is an MCP (Model Context Protocol) server designed to provide AI models with access to Rust crate documentation. It enables lookup of crate-level and item-level documentation, as well as efficient searching of Rust crates on crates.io. The system supports various server modes, offers multiple output formats, and includes features for both developers and large language models.

• ⭐ 9
• MCP
• PromptExecution/cratedocs-mcp

dbt-docs-mcp implements a Model Context Protocol (MCP) server that interacts with dbt project metadata artifacts such as manifest.json and catalog.json. It exposes the dbt project graph through a standardized API, enabling search and inspection of models, sources, columns, and their upstream/downstream lineage. The solution facilitates column-level and model-level lineage analysis, node inspection, and can be extended to support database metadata querying and custom knowledge bases. It is designed for integrations with MCP-compatible clients, supporting advanced data discovery and context sharing workflows.

• ⭐ 21
• MCP
• mattijsdp/dbt-docs-mcp

Rust Docs MCP Server provides AI coding assistants with a focused tool to query current documentation for specific Rust crates. It runs as a standard MCP server over stdio, enabling context-driven semantic searches and LLM-generated answers based only on retrieved documentation. It fetches crate docs, generates embeddings, and leverages OpenAI APIs for accurate and relevant code support, with support for caching and multi-crate operation.

• ⭐ 208
• MCP
• Govcraft/rust-docs-mcp-server

Unified Diff MCP Server provides a powerful tool for visualizing code diffs in an engaging HTML format, tailored for use with Claude Desktop. It supports sharing diffs via GitHub Gist, saving outputs as PNG or HTML files, and features auto-delete and multi-level security. Designed for high performance and cross-platform compatibility, it makes code review and sharing diffs efficient and visually appealing.

• ⭐ 8
• MCP
• gorosun/unified-diff-mcp

Qlik MCP Server enables integration between Claude AI and Qlik Cloud applications through the Model Context Protocol (MCP). It exposes API tools for listing Qlik apps, retrieving sheets and charts, and extracting chart data programmatically. The server supports deployment via Docker, Deno, or Node.js, and can be configured for use with tools like Claude Desktop and Cursor. The setup emphasizes secure handling of Qlik Cloud credentials and flexible environment configuration.

• ⭐ 7
• MCP
• jwaxman19/qlik-mcp

Firefly MCP Server is a TypeScript-based server implementing the Model Context Protocol to enable integration with the Firefly platform for discovering and managing resources across Cloud and SaaS accounts. It supports secure authentication, resource codification into infrastructure as code, and easy integration with tools such as Claude and Cursor. The server can be configured via environment variables or command line and communicates using standardized MCP interfaces. Its features facilitate automation and codification workflows for cloud resource management.

• ⭐ 15
• MCP
• gofireflyio/firefly-mcp

Databricks MCP Server implements the Model Context Protocol (MCP) to provide a bridge between Databricks APIs and large language models. It enables LLMs to run SQL queries, list Databricks jobs, retrieve job statuses, and fetch detailed job information via a standardized MCP interface. The server handles authentication, secure environment configuration, and provides accessible endpoints for interaction with Databricks workspaces.

• ⭐ 42
• MCP
• JordiNeil/mcp-databricks-server

Flowcore Platform MCP Server provides an implementation of the Model Context Protocol (MCP) for seamless interaction and management of Flowcore resources. It enables AI assistants to query and control the Flowcore Platform using a structured API, allowing for enhanced context handling and data access. The server supports easy deployment with npx, npm, or Bun and requires user authentication using Flowcore credentials.

• ⭐ 9
• MCP
• flowcore-io/mcp-flowcore-platform

Framelink MCP for Figma enables AI-powered coding tools to access and process context-rich Figma design data through the Model Context Protocol. It serves as a mediator, simplifying and translating Figma API responses into concise, relevant layout and styling information tailored for model consumption. The tool is designed for integration with editors like Cursor, helping AI agents accurately implement designs in various frameworks from Figma links. It also supports straightforward configuration for different platforms with personal Figma access tokens.

• ⭐ 11,747
• MCP
• GLips/Figma-Context-MCP

GitKraken CLI provides an advanced command-line interface for managing multiple Git repositories and work items efficiently. It includes a local MCP server, enabling seamless integration with git, GitHub, Jira, and compatibility with tools leveraging LLMs. The tool supports AI-powered commit messages, pull request generation, and robust context handling for collaborative and multi-repo workflows. Installation is available for macOS, Windows, and Unix systems.

• ⭐ 316
• MCP
• gitkraken/gk-cli

dbt MCP Server provides an implementation of the Model Context Protocol for dbt projects, enabling seamless integration between dbt and AI agents. It allows agents to access and understand the context of dbt Core, dbt Fusion, and dbt Platform projects. The tool supports connection to external AI products and offers resources for building custom agents. Documentation and examples are provided to facilitate adoption and integration.

• ⭐ 420
• MCP
• dbt-labs/dbt-mcp