"Information about Gemini code" matching MCP servers:

Gives AI assistants read access to SDLC project artifacts stored in Supabase, enabling natural language queries about projects, artifacts, screens, and tech stacks, with optional IT cost estimation via Vertex AI Gemini.

MCP server integrating OBSS Timepiece Time in Status for Jira, enabling queries about issue durations, status histories, and aggregated metrics via natural language.

A read-only MCP server that gives LLM agents deterministic operational facts about Trello boards, including structural history, card movement, workflow flow, staleness, and due-date information.

One local MCP server that lets Codex and Claude Code coordinate through a shared task board and message inbox.

Enables any MCP-capable coding agent to gate code writing behind user-approved design checkpoints, asking for the user's own approach first and recording decisions, project maps, and progress in a local .vibe-wise/ folder. Code is only written once the user explicitly confirms an implementation checkpoint, with no account, backend, or telemetry required.

Enables Claude Code to interact with Azure DevOps Server on-premises (work items, pull requests, repositories) through secure, controlled, safe-by-default access with read-only mode and explicit write confirmations.

A Model Context Protocol (MCP) server for GitLab and Jira integration. This server allows AI agents like gemini-cli to interact with your GitLab and Jira instances.

A Model Context Protocol (MCP) server for Trello that works with any MCP-compatible client -- Claude Desktop, Claude Code, Gemini CLI, and more. Provides 46 tools covering boards, cards, lists, labels, checklists, attachments, members, custom fields, and search.

Provides capabilities for searching Jira issues using JQL and retrieving detailed issue information.

Read-only MCP bridge connecting Claude Desktop to Merlin Project on Mac, allowing natural-language queries about plans, activities, resources, and project data.

Connects your Ashby recruiting data to Claude, enabling natural language queries and management of candidates, applications, jobs, interviews, offers, and team information.

Model Context Protocol (MCP) server for ERPNext - manage timesheets, leave applications, projects, and software releases via Claude, Gemini, or any MCP-compatible AI assistant.

Enables Claude to read and analyze project schedule files in OmniPlan (.oplx) and Microsoft Project (.mpp) formats, answering questions about tasks, milestones, resources, and progress.

Enables AI assistants to securely connect to OpenProject workspaces and browse, query, and reason about projects, work packages, saved queries, and related metadata via the OpenProject REST API v3.

Captures comprehensive context about development issues and facilitates human assistance through structured API-based help requests.

Enables AI assistants to research, plan and manage tasks, generate requirements and user stories, scaffold projects, analyze codebases, curate context, and run multi-step development workflows.

Enables AI assistants to research, plan, generate requirements, user stories, task lists, and full-stack starter projects, analyze codebases, curate context, and run multi-step software development workflows through MCP tools.

Paid remote MCP for generating trustworthy code run receipts, scope summaries, missing evidence checks, and client handoff exports.

Enables AI assistants and MCP-compatible clients to research, plan, generate requirements, analyze codebases, manage tasks, create user stories, and scaffold full-stack starter projects through specialized development tools.

Equips AI assistants and MCP clients with software development tools for deep research, codebase mapping, context curation, and multi-step workflow execution. It also generates product requirements documents, user stories, task lists, and fullstack starter projects.

Equips MCP-compatible AI assistants with tools for deep research, requirements and PRD generation, codebase mapping, context curation, task management, and fullstack starter-project scaffolding. It supports CLI, REPL, and server modes so developers can drive software development workflows through natural-language commands.

Enables read-only intelligence over a Linear workspace by serving snapshot and change-history data stored in Cloudflare D1, so clients can answer questions about current work, project and milestone progress, member activity, and weekly reports without modifying Linear or invoking an LLM.

Enables Codex and other MCP clients to read kickoff cards, acceptance criteria, Git evidence, and next steps, then append validated, audited progress events for resumable project handoffs.

Enables agents to create, move, annotate, question, block and archive tasks on a four-column board whose state is written as an atomic JSON file inside the repository, so tracking survives restarts and appears in code review. A human approval boundary requires user confirmation for approvals and rejections, keeping agents from closing their own review items.

Enables coordinating two coding agents through a shared SQLite task pool with an explicit review workflow, allowing agents to query, claim, submit, review, and approve or reject tasks while enforcing reviewer and iteration safeguards.

Collects and aggregates developer activity data from GitLab, GitHub, Google Calendar, and Outlook Calendar. Enables tracking of commits, pull requests, code reviews, issues, and meeting information across multiple platforms with secure OAuth authentication.

A zero-dependency MCP server that answers common questions about Jira work, such as what is assigned to me, standup status, sprint health, and more, without returning raw issue JSON.

Enables AI assistants to research topics, generate product requirements and user stories, map codebases, curate context, scaffold full-stack starter projects, and run multi-step development workflows.

Enables Codex to interact with OpenProject for project management, work packages, and reporting.

Enables AI assistants such as Claude Desktop to access and manage amoCRM data—including leads, contacts, companies, tasks, pipelines, users, notes, and account information—through stdio or Streamable HTTP transports.