Bitbucket Server MCP is an MCP (Model Context Protocol) server designed to facilitate Bitbucket Server Pull Request management. It provides tools and resources to interact with the Bitbucket Server API through the MCP protocol, enabling actions such as creating, retrieving, merging, and declining pull requests, as well as adding comments and fetching diffs or reviews.
Bitbucket Server MCP simplifies interactions with Bitbucket Server by offering a structured way to manage pull requests and related workflows via the MCP protocol. It supports features like default project configuration, various merge strategies, and detailed logging for monitoring and debugging purposes, making it ideal for developers who want seamless integration with Bitbucket Server.
Developers and DevOps teams managing Bitbucket Server repositories will benefit from this tool. It is particularly useful for those who need programmatic access to Bitbucket's APIs for automating PR workflows, integrating with CI/CD pipelines, or enhancing their development processes.
Bitbucket Server MCP can be installed either manually via npm or automatically using Smithery. The installation requires Node.js >= 16, and the server can be configured in VSCode MCP settings or through environment variables.
Bitbucket Server MCP should be used when there is a need to programmatically manage Bitbucket Server pull requests, automate workflows, or integrate Bitbucket functionality into custom applications or tools. Its logging and configuration capabilities also make it suitable for environments requiring detailed operation tracking.
Key features include creating, retrieving, merging, and declining pull requests; adding comments; fetching diffs and reviews; support for multiple merge strategies; and configurable default project settings.
You can install it manually by running `npm install` or automatically via Smithery using the command `npx -y @smithery/cli install @garc33/bitbucket-server-mcp-server --client claude`. Ensure you have Node.js >= 16 installed.
It relies on `@modelcontextprotocol/sdk` for MCP protocol implementation, `axios` for HTTP requests, and `winston` for logging.
Configuration is done in the VSCode MCP settings file or via environment variables like `BITBUCKET_URL`, `BITBUCKET_TOKEN` (or username/password), and optionally `BITBUCKET_DEFAULT_PROJECT`.
The `smithery.yaml` file contains configuration details for Smithery, which is used to simplify the installation process of Bitbucket Server MCP.
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
At mcpserver.shop, you can browse our MCP Server Directory. The directory is categorized by industry (e.g., finance, healthcare, education), and each server comes with detailed descriptions and tags to help you quickly find the option that suits your needs.
The MCP Server Directory on mcpserver.shop is free to browse. However, some servers are hosted by third-party providers and may involve usage fees. Check the detailed page of each server for specific information.
MCP Servers support a wide range of data sources, including databases, APIs, cloud services, and custom tools. The flexibility of the MCP protocol allows it to connect almost any type of data source to AI models.
MCP Servers are primarily designed for developers, data scientists, and AI app builders. However, mcpserver.shop provides detailed documentation and guides to help users of varying technical levels get started easily.
Yes, MCP is an open-source protocol that encourages community participation and collaboration. For more details or to contribute, visit the official MCP documentation.
On mcpserver.shop, each MCP Server’s detailed page includes the provider’s contact information or a link. You can directly reach out to the provider for more details or technical support.