"File reading, writing, searching, analysis and interpretation" matching MCP servers:

A powerful Model Context Protocol (MCP) server for seamless Jira integration with AI assistants like Claude. Features advanced search capabilities, intelligent pod aliases, comprehensive ticket analysis, and full API support.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables the analysis of GitHub Pull Requests to extract metadata, commits, and code changes for structured AI insights. It also supports the optional creation of Notion pages to store and organize the resulting analysis.

Enables AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.

Enables agents to read and report, and to carry human-authored updates into systems of record after human consent, while structurally preventing autonomous writes of commitments like owners, due dates, or statuses.

Fast native Swift OmniFocus MCP server and CLI for macOS. Let AI assistants safely read, update, complete, and organize tasks and projects through documented Omni Automation APIs.

A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.

Provides AI clients with per-project todo management and persistent context notes via MCP, enabling task tracking and resume summaries.

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.

MCP server that connects AI coding tools to VibeCompass projects for reading context and writing decisions, conflicts, and session notes.

A local Model Context Protocol server for monday.com that translates plain column values into the exact API shapes monday.com stores, with column-title-aware tools for reading and writing boards, items, updates, and users plus safety rails like read-only mode and board allow lists.

Provides AI assistants with direct access to MantisBT issue trackers via the REST API, enabling reading, updating, resolving, and semantically searching issues.

A lightweight Jira Cloud MCP server for Claude Code that provides high-value tools for reading and writing Jira issues with human-readable responses.

An unofficial MCP server that enables AI assistants to work with Yandex Tracker, Yandex Mail, and Yandex Calendar on the user's behalf, supporting reading, writing, and workflow automations such as meeting follow-ups, standups, and email-to-task creation.

Enables reading, listing, searching, commenting on, and updating status of ZenTao bugs via its REST API, with write operations defaulting to dry-run.

Exposes Zentao REST API as MCP tools for listing/searching bugs, reading details with screenshots, and resolving bugs after explicit confirmation. Includes a setup wizard to configure Codex, Claude, Cursor and other clients.

MCP server for Jira integration with stdio transport. Enables reading, writing, and managing Jira issues and projects directly from Claude Desktop. Supports issue creation, updates, comments, JQL search, and project management.

MCP server to manage GestSup tickets via an LLM, with tools for creating, reading, commenting, and searching tickets.

Enables AI agents to manage osTicket support tickets including listing, searching, reading, creating, updating, replying, deleting, managing subtickets, and downloading attachments.

Enables reading and writing Zendesk tickets, including searching, fetching comments, posting replies and internal notes, setting ticket status, assigning tickets, logging time, and formatting tickets as Markdown issue drafts for handoff to GitLab, GitHub, or Jira.

Enables reading and writing Huly documents and issues from MCP clients like Claude Desktop and Claude Code, including document CRUD, search, issue reading, and commenting.

Enables AI assistants to interact with the Clockify API for managing time entries, timers, and team management tasks. It provides tools for searching time records, tracking project hours, and performing high-level analysis like overtime detection and weekly summaries.

Lets an AI assistant read and fill an Innoslate project through your own logged-in browser session, surveying the project, reading your documents and guides, and proposing a plan before writing entities, trace links, artifacts and reports after a dry run. It works on the free tier where API keys are refused, since every call goes through the browser instead.

Manages feature documentation and bug tracking inside an Obsidian vault, organized by project, enabling project listing, feature doc writing, bug filing, status updates, and retrieval.

A local MCP server that enables searching, reading, creating, updating, and commenting on NinjaOne tickets through natural language.

Enables Claude to manage Apple Reminders on macOS, including creating, reading, updating, deleting, and searching reminders across multiple lists with due dates, priorities, and notes.

Enables comprehensive management of Zendesk tickets, comments, and Help Center articles through tools for searching, creating, and updating content. It includes specialized prompts for ticket analysis and response drafting to streamline support workflows.

A Deno implementation that enables AI models to interact with Linear issue tracking functionality, supporting searching issues, reading details, updating, and commenting.