{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-alibabacloud-devops-mcp","slug":"alibabacloud-devops-mcp","name":"AlibabaCloud DevOps MCP","type":"mcp","url":"https://github.com/aliyun/alibabacloud-devops-mcp-server","page_url":"https://unfragile.ai/alibabacloud-devops-mcp","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-alibabacloud-devops-mcp__cap_0","uri":"capability://tool.use.integration.mcp.based.devops.tool.registration.and.protocol.bridging","name":"mcp-based devops tool registration and protocol bridging","description":"Implements the Model Context Protocol (MCP) as a standardized interface layer that registers DevOps tools (Codeup, Projex, Flow) and translates AI assistant requests into structured tool invocations. The server uses a tool registry pattern where each tool is defined with JSON schemas and mapped to implementation functions, enabling AI assistants like Cursor and Tongyi Lingma to discover and call DevOps operations through a unified protocol without direct API knowledge.","intents":["Enable AI assistants to discover available DevOps operations without hardcoding API details","Standardize how AI tools invoke Yunxiao platform capabilities across different assistant implementations","Provide schema-based tool definitions so AI models understand parameter requirements and return types"],"best_for":["Teams using Alibaba Cloud Yunxiao and wanting AI-assisted DevOps workflows","AI assistant developers integrating with Alibaba Cloud ecosystems","Organizations standardizing on MCP for DevOps automation"],"limitations":["MCP protocol overhead adds latency per tool invocation compared to direct API calls","Tool discovery is static at server startup — dynamic tool registration not supported","Limited to tools explicitly registered in the server initialization phase"],"requires":["Go 1.16+ (for server compilation)","Yunxiao API access token (YUNXIAO_ACCESS_TOKEN environment variable)","AI assistant with MCP client support (Cursor, Tongyi Lingma, or compatible)"],"input_types":["JSON-formatted tool parameters matching registered schemas"],"output_types":["JSON-structured tool responses","Error messages with context"],"categories":["tool-use-integration","devops-platforms"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_1","uri":"capability://tool.use.integration.repository.management.with.branch.and.file.operations","name":"repository management with branch and file operations","description":"Exposes Codeup (Alibaba's code management service) operations through MCP tools that enable AI assistants to create/delete branches, read/write files, list repositories, and manage repository metadata. The implementation wraps Yunxiao API calls through the YunxiaoClient, translating high-level repository operations (e.g., 'create_branch') into authenticated HTTP requests with proper error handling and response parsing.","intents":["Create and manage Git branches programmatically from AI assistant context","Read source code files to provide context for code generation or analysis","Write generated code or modifications back to repositories without manual file operations","List and discover repositories available in the Yunxiao workspace"],"best_for":["AI-assisted code generation workflows requiring direct repository writes","Developers wanting AI to manage branch lifecycle (create feature branches, cleanup)","Teams automating code review preparation through AI-driven file modifications"],"limitations":["File operations limited to text-based content — binary files not supported","No built-in merge conflict resolution — concurrent writes may fail","Branch operations are synchronous — no async job tracking for long-running operations","File size limits inherited from Yunxiao API (typically 100MB per file)"],"requires":["Yunxiao API access token with Codeup permissions","Repository must exist in Yunxiao workspace","Git repository initialized in Yunxiao (not raw file storage)"],"input_types":["Repository ID (string)","Branch name (string)","File path (string)","File content (text)","Commit message (string)"],"output_types":["Branch metadata (name, commit hash, creation timestamp)","File content (text)","Repository list with metadata","Commit confirmation with hash"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_10","uri":"capability://tool.use.integration.error.handling.and.response.formatting","name":"error handling and response formatting","description":"Implements consistent error handling across all tool invocations, translating Yunxiao API errors into structured MCP error responses with context and actionable messages. The error handling layer catches API failures, network errors, and validation errors, formatting them as MCP-compliant error responses that AI assistants can interpret and act upon.","intents":["Provide clear error messages when tool invocations fail","Enable AI assistants to handle errors gracefully and retry appropriately","Translate API-specific errors into user-friendly messages","Log errors for debugging and monitoring"],"best_for":["Teams building reliable AI-assisted workflows that need error recovery","Developers debugging tool failures and API issues","Organizations monitoring MCP server health and reliability"],"limitations":["Error messages are generic — detailed API error codes may be lost in translation","No automatic retry logic — AI assistants must implement retry strategies","Error context limited to error message — stack traces not exposed","No structured error codes — errors are returned as text messages"],"requires":["Proper error handling in tool implementations","Logging infrastructure for error tracking"],"input_types":["Tool invocation requests (JSON-RPC format)"],"output_types":["Error responses (MCP error format)","Error messages (text)","HTTP status codes"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_11","uri":"capability://tool.use.integration.extensible.tool.registration.framework","name":"extensible tool registration framework","description":"Provides a framework for registering new tools with the MCP server through a declarative tool definition and implementation function mapping. The framework allows developers to add new Yunxiao capabilities by defining tool schemas and implementing handler functions, with the server automatically registering tools during initialization without modifying core server logic.","intents":["Add new Yunxiao capabilities to the MCP server without modifying core code","Standardize how new tools are defined and registered","Enable community contributions of new tools","Maintain separation between tool definitions and server infrastructure"],"best_for":["Teams extending MCP server with custom Yunxiao tools","Developers contributing new tools to the open-source project","Organizations building tool ecosystems on top of Yunxiao"],"limitations":["Tool registration is static at server startup — no dynamic tool loading","Tool implementations must follow specific function signature patterns","No built-in tool versioning — multiple versions of same tool not supported","Tool dependencies must be manually managed"],"requires":["Go 1.16+ for tool implementation","Understanding of tool schema definition format","Knowledge of Yunxiao API endpoints being wrapped"],"input_types":["Tool definition (schema, description, parameters)","Implementation function (Go function with specific signature)"],"output_types":["Registered tool available to AI assistants","Tool schema discoverable via MCP protocol"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_2","uri":"capability://tool.use.integration.change.request.and.code.review.workflow.automation","name":"change request and code review workflow automation","description":"Provides MCP tools for creating, listing, and managing change requests (merge requests/pull requests) in Codeup, enabling AI assistants to initiate code review workflows, add reviewers, and track review status. The implementation maps change request operations to Yunxiao API endpoints, handling authentication, request formatting, and response parsing to abstract the underlying REST API complexity.","intents":["Automatically create change requests from AI-generated code with appropriate descriptions","Assign reviewers and set review policies programmatically based on code changes","Query change request status to provide feedback on code review progress","Manage change request lifecycle (open, close, merge) through AI workflows"],"best_for":["Teams automating code review initiation for AI-generated code","CI/CD pipelines that need AI-assisted change request management","Developers wanting AI to handle change request metadata and reviewer assignment"],"limitations":["Change request creation requires source and target branches to exist","No built-in conflict detection — merge conflicts must be resolved manually","Reviewer assignment limited to users with repository access","Change request templates not supported — descriptions are free-form text"],"requires":["Yunxiao API token with Codeup change request permissions","Source and target branches must exist in repository","Reviewer users must have repository access"],"input_types":["Source branch name (string)","Target branch name (string)","Change request title (string)","Change request description (text)","Reviewer user IDs (array of strings)"],"output_types":["Change request ID and metadata","Change request status (open, merged, closed)","Reviewer list with approval status","Merge conflict indicators"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_3","uri":"capability://tool.use.integration.code.comparison.and.diff.analysis","name":"code comparison and diff analysis","description":"Exposes Codeup's code comparison capabilities through MCP tools that generate diffs between branches, commits, or file versions. The implementation calls Yunxiao's diff API endpoints, returning structured diff data that AI assistants can analyze to understand code changes, identify patterns, or generate review comments without requiring local Git diff operations.","intents":["Generate diffs between branches to understand what code changes will be introduced","Analyze code changes programmatically to identify breaking changes or security issues","Provide AI-generated code review comments based on diff analysis","Track code evolution across commits for impact analysis"],"best_for":["AI code review assistants that need to analyze changes before generating feedback","Automated testing systems that need to understand code impact","Documentation generators that track API or interface changes"],"limitations":["Diff output limited to text-based files — binary diffs not supported","Large diffs (>10MB) may be truncated or paginated","Diff context limited to configurable number of lines (typically 3-5 lines before/after)","No support for rename detection — moved files appear as delete + add"],"requires":["Yunxiao API token with Codeup read permissions","Both branches/commits must exist in repository","Repository must be Git-based (not other VCS)"],"input_types":["Source branch/commit (string)","Target branch/commit (string)","Optional: file path filter (string)","Optional: context lines (integer)"],"output_types":["Unified diff format (text)","Structured diff with file-level and hunk-level metadata","Change statistics (files changed, insertions, deletions)"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_4","uri":"capability://tool.use.integration.project.and.work.item.management","name":"project and work item management","description":"Exposes Projex (Alibaba's project management service) operations through MCP tools for creating, listing, and updating work items (tasks, bugs, features) and managing project metadata. The implementation wraps Projex API calls through YunxiaoClient, translating work item operations into authenticated requests with support for custom fields, status transitions, and assignment workflows.","intents":["Create work items automatically from AI-identified issues or feature requests","Query project work items to understand current development status and priorities","Update work item status and assignments based on development progress","Link work items to code changes for traceability"],"best_for":["Teams wanting AI to auto-create issues from code analysis or user feedback","Project managers using AI to track development status across repositories","Developers automating work item lifecycle management"],"limitations":["Work item creation requires project to exist and be accessible","Custom fields must be pre-configured in Projex — dynamic field creation not supported","Status transitions limited to configured workflow states","No bulk operations — work items must be created/updated individually"],"requires":["Yunxiao API token with Projex permissions","Project must exist in Yunxiao workspace","User must have project access"],"input_types":["Project ID (string)","Work item type (string: task, bug, feature, etc.)","Title (string)","Description (text)","Assignee user ID (string)","Priority (enum: low, medium, high)","Custom fields (key-value pairs)"],"output_types":["Work item ID and metadata","Work item status and workflow state","Assignment and priority information","Custom field values"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_5","uri":"capability://tool.use.integration.sprint.planning.and.iteration.management","name":"sprint planning and iteration management","description":"Provides MCP tools for managing sprints in Projex, including creating sprints, assigning work items to sprints, and tracking sprint progress. The implementation calls Projex sprint APIs to handle sprint lifecycle (planning → active → closed) and work item allocation, enabling AI assistants to optimize sprint planning and capacity management.","intents":["Create new sprints and configure sprint parameters (duration, goals, capacity)","Assign work items to sprints based on priority and team capacity","Query sprint status and progress metrics for reporting","Manage sprint transitions (start, close, archive)"],"best_for":["Scrum masters wanting AI-assisted sprint planning","Teams automating sprint setup and work item allocation","Project managers tracking sprint velocity and burndown"],"limitations":["Sprint duration must follow configured sprint templates","Work item assignment to sprints requires work items to exist first","No automatic capacity calculation — must be manually configured","Sprint closure is irreversible — closed sprints cannot be reopened"],"requires":["Yunxiao API token with Projex sprint management permissions","Project must have sprint templates configured","Work items must exist before sprint assignment"],"input_types":["Project ID (string)","Sprint name (string)","Sprint start date (ISO 8601)","Sprint end date (ISO 8601)","Sprint goal (text)","Work item IDs for assignment (array of strings)"],"output_types":["Sprint ID and metadata","Sprint status (planning, active, closed)","Work item assignments and capacity metrics","Sprint progress and burndown data"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_6","uri":"capability://tool.use.integration.ci.cd.pipeline.execution.and.monitoring","name":"ci/cd pipeline execution and monitoring","description":"Exposes Flow (Alibaba's CI/CD service) operations through MCP tools for listing pipelines, triggering pipeline executions, and monitoring build status. The implementation wraps Flow API calls through YunxiaoClient, translating pipeline operations into authenticated requests with support for parameterized builds and real-time status tracking.","intents":["Trigger CI/CD pipelines automatically from AI workflows or code changes","Query pipeline execution status to provide build feedback to developers","Monitor build failures and provide AI-generated diagnostics","Parameterize pipeline runs with environment variables or build configurations"],"best_for":["Teams automating CI/CD triggering from AI-assisted code generation","Developers wanting AI to monitor build status and report failures","DevOps engineers automating deployment workflows"],"limitations":["Pipeline execution is asynchronous — no blocking wait for completion","Pipeline parameters must be pre-configured in Flow — dynamic parameter injection limited","Build logs are streamed separately — not included in status responses","No pipeline creation through API — pipelines must be pre-configured in Flow UI"],"requires":["Yunxiao API token with Flow permissions","Pipeline must exist and be configured in Flow","Repository must be connected to Flow"],"input_types":["Pipeline ID (string)","Optional: branch name (string)","Optional: pipeline parameters (key-value pairs)","Optional: environment variables (key-value pairs)"],"output_types":["Pipeline execution ID","Execution status (pending, running, success, failure)","Build metadata (start time, duration, commit hash)","Failure reason and error logs"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_7","uri":"capability://tool.use.integration.dual.transport.protocol.support.stdio.and.sse","name":"dual transport protocol support (stdio and sse)","description":"Implements both stdio (standard input/output) and Server-Sent Events (SSE) transport modes for MCP communication, allowing flexible deployment scenarios. The server initialization logic selects transport based on command-line flags, with stdio providing direct process communication for local AI assistants and SSE enabling network-based communication for remote or web-based AI tools.","intents":["Support local AI assistants (Cursor, local LLMs) using stdio for direct process communication","Enable remote AI assistants to connect via HTTP/SSE without direct process access","Allow flexible deployment in containerized or serverless environments"],"best_for":["Teams deploying MCP server locally with Cursor or similar tools","Organizations running MCP server in containers or cloud environments","Developers needing flexible transport options for different deployment scenarios"],"limitations":["Stdio mode requires process-level access — not suitable for remote deployments","SSE mode adds HTTP overhead and requires network connectivity","Transport mode is selected at server startup — cannot switch modes dynamically","SSE mode requires CORS configuration for browser-based AI assistants"],"requires":["Go 1.16+ for server compilation","For stdio: direct process spawning capability","For SSE: HTTP server listening capability (default: localhost:8000)"],"input_types":["Command-line flag: --transport (stdio|sse)","Command-line flag: --sse-address (host:port for SSE mode)"],"output_types":["MCP protocol messages (JSON-RPC 2.0 format)","Tool responses and error messages"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_8","uri":"capability://tool.use.integration.yunxiao.api.client.abstraction.with.authentication","name":"yunxiao api client abstraction with authentication","description":"Provides YunxiaoClient as a centralized HTTP client for all Yunxiao API interactions, handling authentication token management, request formatting, error handling, and response parsing. The client abstracts API endpoint details and authentication complexity, allowing tool implementations to focus on business logic rather than HTTP mechanics.","intents":["Centralize authentication token management across all Yunxiao API calls","Handle API request/response formatting and error translation","Provide consistent error handling and retry logic for API calls","Abstract API endpoint URLs and versioning"],"best_for":["Developers extending the MCP server with new Yunxiao tools","Teams maintaining consistency in API error handling across tools","Organizations standardizing on Yunxiao API patterns"],"limitations":["Authentication token must be provided at server startup — no dynamic token refresh","No built-in rate limiting — relies on Yunxiao API rate limits","Error responses are translated to generic error messages — detailed API errors may be lost","No request caching — each tool invocation makes fresh API calls"],"requires":["Yunxiao API access token (YUNXIAO_ACCESS_TOKEN environment variable)","Yunxiao API base URL (default: https://openapi-rdc.aliyuncs.com)","Network connectivity to Yunxiao API endpoints"],"input_types":["API endpoint path (string)","HTTP method (GET, POST, PUT, DELETE)","Request body (JSON)","Query parameters (key-value pairs)"],"output_types":["Parsed JSON response","HTTP status codes","Error messages with context"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-alibabacloud-devops-mcp__cap_9","uri":"capability://tool.use.integration.tool.schema.definition.and.discovery","name":"tool schema definition and discovery","description":"Defines tools with JSON schemas that describe parameters, return types, and descriptions, enabling AI assistants to understand tool capabilities and constraints without documentation. The schema-based approach uses standard JSON Schema format, allowing AI models to validate inputs and generate appropriate tool calls based on schema constraints.","intents":["Enable AI assistants to discover available tools and their parameters automatically","Provide schema validation for tool parameters before execution","Generate AI-friendly documentation from tool schemas","Allow AI models to reason about tool capabilities and constraints"],"best_for":["AI assistants that need to understand tool capabilities without hardcoding","Teams building extensible tool systems with dynamic discovery","Developers wanting schema-driven tool development"],"limitations":["Schema definitions must be manually maintained — no automatic schema generation from code","Complex nested schemas may be difficult for AI models to parse","Schema validation is performed by AI assistant — server does not validate inputs against schema","No support for conditional schemas — all parameters are treated independently"],"requires":["JSON Schema format knowledge for tool definition","Tool implementations matching schema parameter names","AI assistant with MCP schema parsing support"],"input_types":["Tool definition (JSON with schema, description, parameters)"],"output_types":["Tool schema (JSON Schema format)","Tool description (markdown text)","Parameter documentation"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":31,"verified":false,"data_access_risk":"high","permissions":["Go 1.16+ (for server compilation)","Yunxiao API access token (YUNXIAO_ACCESS_TOKEN environment variable)","AI assistant with MCP client support (Cursor, Tongyi Lingma, or compatible)","Yunxiao API access token with Codeup permissions","Repository must exist in Yunxiao workspace","Git repository initialized in Yunxiao (not raw file storage)","Proper error handling in tool implementations","Logging infrastructure for error tracking","Go 1.16+ for tool implementation","Understanding of tool schema definition format"],"failure_modes":["MCP protocol overhead adds latency per tool invocation compared to direct API calls","Tool discovery is static at server startup — dynamic tool registration not supported","Limited to tools explicitly registered in the server initialization phase","File operations limited to text-based content — binary files not supported","No built-in merge conflict resolution — concurrent writes may fail","Branch operations are synchronous — no async job tracking for long-running operations","File size limits inherited from Yunxiao API (typically 100MB per file)","Error messages are generic — detailed API error codes may be lost in translation","No automatic retry logic — AI assistants must implement retry strategies","Error context limited to error message — stack traces not exposed","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.49,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:02.370Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=alibabacloud-devops-mcp","compare_url":"https://unfragile.ai/compare?artifact=alibabacloud-devops-mcp"}},"signature":"0vMh7d+KUuMPFYfAX0TXtU1uhMl8xk+1g7kjkmbBVSNTcoBVJ6qdrk8cJXWI1uPBYrFoxljexjXDrV5/ry7qAQ==","signedAt":"2026-06-21T05:00:13.296Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/alibabacloud-devops-mcp","artifact":"https://unfragile.ai/alibabacloud-devops-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=alibabacloud-devops-mcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}