{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"gitlab-mcp-server","slug":"gitlab-mcp-server","name":"GitLab MCP Server","type":"mcp","url":"https://github.com/modelcontextprotocol/servers/tree/main/src/gitlab","page_url":"https://unfragile.ai/gitlab-mcp-server","categories":["mcp-servers"],"tags":["gitlab","devops","ci-cd","official"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"gitlab-mcp-server__cap_0","uri":"capability://tool.use.integration.gitlab.repository.context.exposure.via.mcp.protocol","name":"gitlab repository context exposure via mcp protocol","description":"Exposes GitLab repository metadata, file contents, and commit history as MCP Resources, allowing LLM clients to access repository state without direct API calls. Implements the MCP Resources primitive to surface repository roots, file listings, and commit logs as structured context that LLM agents can query and reason over during multi-turn conversations.","intents":["I want my AI agent to understand the current state of a GitLab repository without making separate API calls","I need the LLM to have access to repository structure, recent commits, and file contents as context for code review","I want to expose repository metadata as queryable resources that persist across multiple LLM interactions"],"best_for":["AI agents performing code analysis and review on GitLab repositories","LLM-powered DevOps tools that need repository context without implementing GitLab API clients","Teams building AI-assisted CI/CD workflows that require repository awareness"],"limitations":["Resource exposure is read-only — no mutation of repository state through Resources primitive","Large repositories may exceed context window if full file listings are exposed; requires pagination or filtering","Commit history exposure limited by GitLab API rate limits and pagination depth"],"requires":["GitLab instance (self-hosted or gitlab.com) with API access","Valid GitLab personal access token or OAuth credentials with api scope","MCP client implementation that supports Resources primitive","Network connectivity to GitLab instance"],"input_types":["repository path/identifier","branch/tag reference","file path within repository"],"output_types":["structured repository metadata (JSON)","file contents (text/binary)","commit history (structured data)","branch/tag listings"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_1","uri":"capability://tool.use.integration.merge.request.creation.and.management.via.schema.based.tool.calling","name":"merge request creation and management via schema-based tool calling","description":"Exposes GitLab merge request operations (create, update, approve, merge, close) as MCP Tools with JSON schema validation, enabling LLM agents to manage code review workflows programmatically. Implements schema-based function calling that maps MCP tool schemas to GitLab REST API endpoints, with built-in validation of required fields (title, source branch, target branch) and optional parameters (assignees, labels, description).","intents":["I want an AI agent to create merge requests automatically based on code changes or review findings","I need the LLM to update merge request metadata (assignees, labels, descriptions) without manual intervention","I want to enable AI-assisted merge request approval workflows that validate code quality before human review"],"best_for":["AI-powered code review agents that need to create and manage MRs programmatically","Automated DevOps workflows that require LLM-driven merge request orchestration","Teams building AI assistants for GitLab that need to handle full MR lifecycle"],"limitations":["Merge request creation requires valid source and target branches to exist; cannot create branches via this tool","Approval workflows depend on GitLab project permissions; tool will fail if agent lacks approval rights","Complex merge strategies (squash, rebase) are limited to GitLab's native merge method options","No support for draft merge requests or merge request templates through this interface"],"requires":["GitLab personal access token with api and write_repository scopes","Source and target branches must exist in the repository","Agent must have Developer or Maintainer role in the GitLab project","MCP client that supports Tools primitive with JSON schema validation"],"input_types":["title (string)","source_branch (string)","target_branch (string)","description (string, optional)","assignees (array of user IDs, optional)","labels (array of strings, optional)","merge_when_pipeline_succeeds (boolean, optional)"],"output_types":["merge request object (JSON with id, iid, state, web_url, etc.)","operation status (success/failure with error details)","updated merge request metadata"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_10","uri":"capability://tool.use.integration.release.and.tag.management.with.artifact.exposure","name":"release and tag management with artifact exposure","description":"Exposes GitLab releases and tags as MCP Resources with artifact metadata, enabling LLM agents to query release information and artifact locations. Implements resource URIs that surface release notes, tag information, and associated artifacts (binaries, archives) as queryable context for deployment and distribution workflows.","intents":["I want an AI agent to understand available releases and tags without manual API calls","I need the LLM to query release artifacts and metadata for deployment workflows","I want to enable AI-assisted release management that can reason about version history and artifacts"],"best_for":["AI agents managing software releases and deployments","LLM-powered DevOps platforms that expose release information as context","Teams building AI assistants that need to reason about version history and artifacts"],"limitations":["Release creation and modification are not supported; only read-only exposure","Artifact download URLs are exposed but actual artifact retrieval is not supported through MCP","Release notes are limited to text; rich media (images, videos) in release descriptions are not fully supported","Pre-releases and draft releases may not be exposed depending on project visibility settings"],"requires":["GitLab personal access token with api and read_repository scopes","Developer or higher role to view releases","MCP client supporting Resources primitive","Valid project ID or path"],"input_types":["project_id (integer or path string)","tag_name (string, optional — for specific tag queries)"],"output_types":["release object (JSON with name, description, created_at, author, etc.)","tag object (JSON with name, message, commit, etc.)","artifact metadata (JSON with download URLs, sizes, etc.)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_11","uri":"capability://tool.use.integration.mcp.server.lifecycle.management.and.transport.configuration","name":"mcp server lifecycle management and transport configuration","description":"Implements MCP server initialization, transport configuration (stdio, HTTP, WebSocket), and capability advertisement following the MCP protocol specification. Handles server startup, client connection negotiation, capability discovery, and graceful shutdown with proper error handling and logging.","intents":["I want to deploy a GitLab MCP server that clients can discover and connect to","I need the server to advertise its capabilities (Tools, Resources, Prompts) to MCP clients","I want to configure transport mechanisms (stdio, HTTP) for different deployment scenarios"],"best_for":["Developers deploying GitLab MCP servers in production environments","Teams integrating GitLab MCP with LLM clients (Claude, etc.)","DevOps engineers configuring MCP server infrastructure"],"limitations":["Server discovery is manual; no automatic client-server pairing without configuration","Transport security (TLS for HTTP) must be configured externally; MCP server provides no built-in encryption","Capability advertisement is static; dynamic capability changes require server restart","No built-in load balancing or horizontal scaling; single server instance per deployment"],"requires":["Node.js 18+ (for TypeScript implementation) or Python 3.9+ (for Python implementation)","MCP SDK (TypeScript or Python)","GitLab API credentials (token with api scope)","Network connectivity to GitLab instance"],"input_types":["transport configuration (stdio, HTTP host/port, WebSocket URL)","GitLab instance URL","GitLab API token"],"output_types":["server status (running/stopped)","capability advertisement (JSON with Tools, Resources, Prompts)","connection logs and diagnostics"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_2","uri":"capability://tool.use.integration.issue.tracking.and.lifecycle.management.through.tool.based.operations","name":"issue tracking and lifecycle management through tool-based operations","description":"Exposes GitLab issue operations (create, update, close, reopen, add comments) as MCP Tools with structured schemas, enabling LLM agents to manage issue workflows and track work items. Implements tool schemas that validate issue creation parameters (title, description, labels, assignees) and support state transitions (open/closed) with audit trails through GitLab's native issue API.","intents":["I want an AI agent to create issues automatically from code review findings or bug reports","I need the LLM to update issue metadata (labels, assignees, milestones) based on analysis results","I want to enable AI-assisted issue triage that categorizes and assigns work items without manual intervention"],"best_for":["AI agents performing automated issue creation from code analysis or test failures","LLM-powered DevOps dashboards that need to manage issue lifecycle programmatically","Teams building AI assistants that track and organize work items in GitLab"],"limitations":["Issue creation requires project-level permissions; cannot create issues in projects where agent lacks Developer role","Bulk issue operations are not supported; each issue requires a separate tool invocation","Issue templates and custom fields are not exposed through this interface","No support for issue boards or epic management through tool operations"],"requires":["GitLab personal access token with api scope","Developer or Maintainer role in the target GitLab project","MCP client supporting Tools primitive","Valid project ID or path"],"input_types":["title (string)","description (string, optional)","labels (array of strings, optional)","assignees (array of user IDs, optional)","milestone_id (integer, optional)","issue_type (string: 'issue' or 'incident', optional)"],"output_types":["issue object (JSON with id, iid, state, web_url, created_at, etc.)","operation status (success/failure)","updated issue metadata"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_3","uri":"capability://tool.use.integration.ci.cd.pipeline.monitoring.and.trigger.management.via.tool.operations","name":"ci/cd pipeline monitoring and trigger management via tool operations","description":"Exposes GitLab CI/CD pipeline operations (trigger pipelines, monitor status, retrieve logs, cancel runs) as MCP Tools, enabling LLM agents to orchestrate and observe build workflows. Implements tool schemas that map to GitLab Pipelines API, supporting pipeline creation with variables, status polling, and log retrieval for debugging and automation.","intents":["I want an AI agent to trigger CI/CD pipelines based on code changes or manual requests","I need the LLM to monitor pipeline status and retrieve logs for debugging without manual dashboard access","I want to enable AI-assisted deployment workflows that trigger pipelines and wait for completion"],"best_for":["AI agents orchestrating GitLab CI/CD workflows and deployments","LLM-powered DevOps automation that needs to trigger and monitor builds","Teams building AI assistants that integrate with GitLab's pipeline infrastructure"],"limitations":["Pipeline triggering requires valid .gitlab-ci.yml configuration; malformed configs will fail at GitLab validation","Log retrieval is limited to completed or running pipelines; artifacts must be explicitly requested","Pipeline variables are passed as strings; complex data structures require JSON serialization by the agent","No support for manual approval gates or pipeline scheduling through this interface"],"requires":["GitLab personal access token with api and read_repository scopes","Valid .gitlab-ci.yml file in the repository","Developer or Maintainer role to trigger pipelines","MCP client supporting Tools primitive"],"input_types":["branch (string)","variables (object with key-value pairs, optional)","pipeline_id (integer, for status/log queries)","job_id (integer, for job-specific logs)"],"output_types":["pipeline object (JSON with id, status, created_at, web_url, etc.)","pipeline status (pending/running/success/failed/canceled)","job logs (text)","artifact metadata (JSON)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_4","uri":"capability://tool.use.integration.code.review.automation.with.diff.analysis.and.comment.insertion","name":"code review automation with diff analysis and comment insertion","description":"Exposes merge request diff analysis and comment operations as MCP Tools, enabling LLM agents to review code changes and provide feedback programmatically. Implements tools that retrieve merge request diffs (with line-by-line change context), support adding comments to specific lines or discussions, and enable approval/request-changes workflows through GitLab's review API.","intents":["I want an AI agent to analyze merge request diffs and provide automated code review feedback","I need the LLM to add comments on specific lines of code with suggestions or concerns","I want to enable AI-assisted code quality checks that approve or request changes based on analysis"],"best_for":["AI-powered code review agents that need to analyze diffs and provide feedback","LLM-based quality gates that require automated code analysis before merge","Teams building AI assistants for GitLab that need to participate in code review workflows"],"limitations":["Diff analysis is limited to text-based files; binary files are not supported","Comments can only be added to open merge requests; closed MRs cannot be reviewed","Approval workflows depend on project-level review rules; agent approval may not satisfy merge requirements","Suggestion comments (with auto-apply) are limited to GitLab Premium; basic comments work on all tiers"],"requires":["GitLab personal access token with api scope","Developer or Maintainer role in the project","Open merge request with available diffs","MCP client supporting Tools primitive"],"input_types":["merge_request_iid (integer)","file_path (string, optional — for line-specific comments)","line_number (integer, optional)","comment_text (string)","review_action (string: 'comment', 'approve', 'request_changes', optional)"],"output_types":["diff object (JSON with file changes, additions, deletions, etc.)","comment object (JSON with id, author, created_at, etc.)","review status (approved/changes_requested/commented)"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_5","uri":"capability://tool.use.integration.project.and.group.management.with.configuration.exposure","name":"project and group management with configuration exposure","description":"Exposes GitLab project and group metadata as MCP Resources and management operations as Tools, enabling LLM agents to query project settings, member lists, and permissions. Implements resource URIs for project configuration (visibility, CI/CD settings, webhooks) and tools for updating project metadata, managing members, and configuring integrations.","intents":["I want an AI agent to understand project structure, members, and permissions without manual API calls","I need the LLM to update project settings (visibility, CI/CD variables) based on configuration requirements","I want to enable AI-assisted project onboarding that configures GitLab projects with standard settings"],"best_for":["AI agents managing GitLab project infrastructure and configuration","LLM-powered DevOps platforms that need to expose project metadata as context","Teams building AI assistants for GitLab that handle project lifecycle management"],"limitations":["Project creation is not supported; only existing projects can be managed","Group-level operations are limited to metadata exposure; group creation requires admin access","CI/CD variable management is limited to project-level variables; group-level variables require higher permissions","Webhook configuration is read-only through Resources; webhook creation requires direct API calls"],"requires":["GitLab personal access token with api and read_user scopes","Maintainer or Owner role for project configuration changes","MCP client supporting Resources and Tools primitives","Valid project ID or path"],"input_types":["project_id (integer or path string)","group_id (integer or path string)","visibility (string: 'private', 'internal', 'public', optional)","ci_cd_variables (object with key-value pairs, optional)"],"output_types":["project object (JSON with id, name, visibility, members, etc.)","group object (JSON with id, name, members, etc.)","configuration metadata (JSON)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_6","uri":"capability://tool.use.integration.protected.branch.and.access.control.policy.exposure","name":"protected branch and access control policy exposure","description":"Exposes GitLab protected branch rules and access control policies as MCP Resources, enabling LLM agents to understand merge requirements, approval rules, and branch protection settings. Implements resource URIs that surface protected branch configurations (required approvals, status checks, push restrictions) as queryable context without requiring separate API calls.","intents":["I want an AI agent to understand protected branch rules before creating merge requests","I need the LLM to be aware of approval requirements and status check policies","I want to enable AI-assisted workflows that respect branch protection rules automatically"],"best_for":["AI agents that need to understand merge requirements before creating MRs","LLM-powered DevOps workflows that must respect branch protection policies","Teams building AI assistants that need to reason about access control constraints"],"limitations":["Protected branch rules are read-only through Resources; rule creation/modification requires direct API calls","Rule complexity (multiple approval groups, status checks) may exceed context window if fully exposed","Changes to protection rules are not reflected in real-time; agents may work with stale policy data"],"requires":["GitLab personal access token with api and read_repository scopes","Maintainer or Owner role to view protection rules","MCP client supporting Resources primitive"],"input_types":["branch_name (string)","project_id (integer or path string)"],"output_types":["protected branch object (JSON with name, push_access_level, merge_access_level, etc.)","approval rules (JSON array with required approvals, status checks, etc.)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_7","uri":"capability://tool.use.integration.webhook.and.integration.configuration.exposure","name":"webhook and integration configuration exposure","description":"Exposes GitLab webhook configurations and integration settings as MCP Resources, enabling LLM agents to understand event subscriptions and external system connections. Implements resource URIs that surface webhook URLs, event triggers, and integration metadata without requiring agents to construct API queries.","intents":["I want an AI agent to understand what webhooks are configured and what events they subscribe to","I need the LLM to be aware of external integrations (Slack, Jira, etc.) connected to the project","I want to enable AI-assisted workflows that can reason about event-driven automation"],"best_for":["AI agents that need to understand project event subscriptions and integrations","LLM-powered DevOps platforms that expose webhook configurations as context","Teams building AI assistants that reason about event-driven workflows"],"limitations":["Webhook creation and modification are not supported; only read-only exposure","Webhook secrets and authentication tokens are not exposed for security reasons","Integration configurations are limited to metadata; actual integration state (e.g., Slack channel) is not queryable"],"requires":["GitLab personal access token with api scope","Maintainer or Owner role to view webhook configurations","MCP client supporting Resources primitive"],"input_types":["project_id (integer or path string)"],"output_types":["webhook object (JSON with id, url, events, active status, etc.)","integration object (JSON with name, type, active status, etc.)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_8","uri":"capability://tool.use.integration.gitlab.graphql.query.execution.with.custom.schema.support","name":"gitlab graphql query execution with custom schema support","description":"Exposes GitLab GraphQL API as an MCP Tool, enabling LLM agents to execute custom GraphQL queries against GitLab's data model. Implements a generic GraphQL query tool that accepts query strings and variables, with response parsing and error handling for complex data retrieval scenarios not covered by predefined tools.","intents":["I want an AI agent to execute custom GraphQL queries for complex data retrieval","I need the LLM to fetch data that isn't exposed through predefined MCP tools","I want to enable AI-assisted workflows that can query GitLab's full GraphQL schema"],"best_for":["Advanced AI agents that need access to GitLab's full GraphQL schema","LLM-powered workflows that require complex multi-entity queries","Teams building custom AI assistants with specialized GitLab data requirements"],"limitations":["GraphQL query complexity is limited by GitLab's rate limiting and query depth restrictions","Large result sets may exceed context window; agents must implement pagination","GraphQL schema changes in GitLab updates may break agent queries without warning","Query performance depends on GitLab instance load; no query optimization hints provided"],"requires":["GitLab personal access token with api scope","Knowledge of GitLab's GraphQL schema (documentation required)","MCP client supporting Tools primitive","Understanding of GraphQL query syntax"],"input_types":["query (string — GraphQL query document)","variables (object with query variables, optional)"],"output_types":["GraphQL response (JSON with data and errors fields)","parsed result objects (JSON)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__cap_9","uri":"capability://tool.use.integration.user.and.team.member.management.with.permission.querying","name":"user and team member management with permission querying","description":"Exposes GitLab user and project member metadata as MCP Resources and member management operations as Tools, enabling LLM agents to query team composition and manage access. Implements resource URIs for user profiles and member lists with permission levels, and tools for adding/removing members and updating roles.","intents":["I want an AI agent to understand project team composition and member permissions","I need the LLM to add or remove project members based on onboarding/offboarding workflows","I want to enable AI-assisted access management that updates member roles and permissions"],"best_for":["AI agents managing project team membership and access control","LLM-powered DevOps platforms that expose team composition as context","Teams building AI assistants for GitLab that handle onboarding/offboarding workflows"],"limitations":["Member addition requires the user to already exist in the GitLab instance; user creation is not supported","Permission changes are limited to predefined GitLab roles (Guest, Reporter, Developer, Maintainer, Owner)","Group member operations are not supported; only project-level member management","Member removal may fail if the user is the only Owner; GitLab enforces at least one Owner per project"],"requires":["GitLab personal access token with api and read_user scopes","Maintainer or Owner role to manage project members","MCP client supporting Resources and Tools primitives","Valid project ID or path"],"input_types":["user_id (integer or username string)","access_level (integer: 10=Guest, 20=Reporter, 30=Developer, 40=Maintainer, 50=Owner)","project_id (integer or path string)"],"output_types":["user object (JSON with id, username, name, email, etc.)","member object (JSON with user_id, access_level, created_at, etc.)","operation status (success/failure)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"gitlab-mcp-server__headline","uri":"capability://tool.use.integration.mcp.server.for.gitlab.devops","name":"mcp server for gitlab devops","description":"An official Model Context Protocol (MCP) server designed specifically for the GitLab DevOps platform, enabling seamless management of repositories, CI/CD pipelines, and integrations through REST and GraphQL APIs.","intents":["best MCP server for GitLab","MCP server for DevOps workflows","GitLab integration for CI/CD","how to manage GitLab repositories with MCP","MCP solutions for GitLab pipelines"],"best_for":["GitLab users","DevOps teams"],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":60,"verified":false,"data_access_risk":"high","permissions":["GitLab instance (self-hosted or gitlab.com) with API access","Valid GitLab personal access token or OAuth credentials with api scope","MCP client implementation that supports Resources primitive","Network connectivity to GitLab instance","GitLab personal access token with api and write_repository scopes","Source and target branches must exist in the repository","Agent must have Developer or Maintainer role in the GitLab project","MCP client that supports Tools primitive with JSON schema validation","GitLab personal access token with api and read_repository scopes","Developer or higher role to view releases"],"failure_modes":["Resource exposure is read-only — no mutation of repository state through Resources primitive","Large repositories may exceed context window if full file listings are exposed; requires pagination or filtering","Commit history exposure limited by GitLab API rate limits and pagination depth","Merge request creation requires valid source and target branches to exist; cannot create branches via this tool","Approval workflows depend on GitLab project permissions; tool will fail if agent lacks approval rights","Complex merge strategies (squash, rebase) are limited to GitLab's native merge method options","No support for draft merge requests or merge request templates through this interface","Release creation and modification are not supported; only read-only exposure","Artifact download URLs are exposed but actual artifact retrieval is not supported through MCP","Release notes are limited to text; rich media (images, videos) in release descriptions are not fully supported","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.52,"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":"2026-06-17T09:51:04.691Z","last_scraped_at":null,"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=gitlab-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=gitlab-mcp-server"}},"signature":"wjE7Ag91w/oMGh8QCcKvWsXKlhZeHweDif/bE6EiL3sC8ro1eKjUv8hJ5wU7cCaWPBBT9PxSUc+h8Z47tmbKBQ==","signedAt":"2026-06-21T15:28:28.656Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/gitlab-mcp-server","artifact":"https://unfragile.ai/gitlab-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=gitlab-mcp-server","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"}}