dev.mcp
Related Servers
Alternatives to dev.mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityBmaintenanceA single MCP server that runs many bundled integrations — GitHub, GitLab, Jira, Confluence — from declarative JSON manifests, exposing all of their tools over one stdio connection. It enables discovering repositories, issues, merge requests, pages and pipelines, and creating or transitioning them, with per-server authentication handled by the executor.MIT
- FlicenseNot gradedqualityDmaintenanceA modular MCP server exposing tools for integrating with services like GitHub, Redash, Jenkins, Figma, Jira, Confluence, Teams, Datadog, PagerDuty, Slack, and Presto, enabling users to manage these platforms through natural language via an MCP client.-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents and MCP clients to manage projects, merge requests, issues, pipelines, wiki, releases, tags, milestones, and more through stdio, SSE, or Streamable HTTP with PAT/OAuth authentication.189,695 npmMIT
- AlicenseNot gradedqualityDmaintenanceUnified MCP server that integrates Jira, GitLab, and Confluence for AI assistants to access project management, code repositories, and documentation from a single interface.MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that enables interaction with Jira to fetch issues by key and perform JQL searches. It provides a foundation for integrating multiple work systems, with planned support for Slack and GitHub.1,082 npmMIT
- AlicenseNot gradedqualityDmaintenanceEnables AI coding assistants to search, create, update, and manage Jira issues, users, and projects via natural language, using the Jira REST API and MCP stdio transport.1,082 npmMIT
TDQS
Scored across 55 tools
Tools are grouped by product prefix and target distinct resource/action pairs, so most are easy to tell apart even at 55 tools. The main risk is within Figma where get_file/get_metadata/get_design_context and get_screenshot/download_assets have adjacent image/export purposes, though the descriptions provide enough separation.
Nearly all tools follow a product_verb_noun snake_case pattern (confluence_create_page, jira_transition_issue), which is highly predictable. Deviations like figma_whoami/gitlab_whoami and the ambiguous gitlab_save_merge_request (create-or-update) keep it from a perfect score.
At 55 tools this server presents an extreme selection burden, far beyond the 25+ threshold; it effectively bundles four product-specific servers into one namespace. The per-platform subsets are reasonable, but the aggregate would be better split into separate MCP servers.
Core lifecycles are covered for all four platforms: Confluence pages/comments, GitLab MRs/issues/pipelines/files, Jira issues/transitions/comments/worklogs/links, and Figma read/export/context. Missing operations are mostly destructive ones (deletes, comment updates) that can be worked around or are rarely needed in AI-assisted dev workflows.