"A tool for reading Jira ticket content" matching MCP servers:

Enables searching and retrieving only human-confirmed issue-ticket knowledge, submitting draft tickets, and recording feedback with aggregated statistics through MCP tools.

Provides content agents with structured search over editorial guidelines, visual templates, and past post outcomes, enabling auditable proposals that cite rule IDs.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables MCP clients to search, read, and modify self-hosted Jira and Confluence Server/Data Center content through per-user authenticated REST API tools, including issues, pages, comments, workflows, boards, sprints, and custom endpoints.

Content Registry - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables comprehensive content management through Markdown processing, HTML rendering, intelligent fuzzy search, and document analysis. Supports frontmatter parsing, tag-based filtering, table of contents generation, and directory statistics for efficient content organization and discovery.

Enables coding agents to turn Jira Cloud tickets into ready-to-build briefs, verify local branches against acceptance criteria, and prepare QA handoffs, with optional previewed and audited write-back.

This MCP server provides unified read/write access to Jira Cloud tickets and Confluence Cloud pages, enabling search, retrieval, and updates. It automatically downloads log attachments from tickets into a shared directory for the companion Log Intelligence MCP to ingest.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.

A Bun-based MCP server that allows AI models to query Swagger/OpenAPI documentation from local files or remote URLs. It enables users to search for APIs, retrieve detailed endpoint definitions, and fetch schemas to facilitate code generation and API integration.

An MCP server that helps transfer C4 diagrams from DrawIO and PlantUML into a DocHub architecture repository.

Enables AI clients to access and manage an internal support ticket queue through MCP tools, resources, and prompts, including searching and viewing tickets, adding comments, closing tickets with confirmation, reading knowledge base articles, and viewing queue summaries over OAuth-secured Streamable HTTP.

Optimizes EDT MCP tool descriptions by replacing verbose documentation with concise summaries stored in SQLite, reducing context usage while allowing on-demand retrieval of full tool guides.

Read-only MCP server for a content contract layer: protocol, modules, pipelines, assets, library. 一句话 / One-liner（ZH）：给任何 AI agent 一个可校验的内容规范与资产底座——先查契约，再落笔。 描述 / Description：只读 MCP 服务器：把长内容的验收标准（协议 / 模块 / 管线 / 资产 / 馆藏）变成 agent 可调用的检索与取件工具面。10 个只读工具 + 1 个 prompt（assemble_guide）；支持 modern 2026-07-28 与 legacy 2025-11-25 双协议；零第三方依赖（Python 标准库）；无写路径。 仓库 / Repo：https://github.com/Monyeah777/NinFenz 站点

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

Provides controlled, verifiable access to jw.org content for AI applications, enabling search, article retrieval, and scripture lookup while preventing hallucinations.

Provides AI assistants with locally bundled tools to explore NIST OSCAL models, retrieve schemas, list community resources, and generate valid OSCAL templates for governance, risk, and compliance workflows.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

Enables comprehensive content analysis through web scraping, document processing (PDF, DOCX, TXT, RTF), screenshot analysis, and local Excel database management. Provides intelligent workflows for extracting, analyzing, and storing content from multiple sources with automated categorization and search capabilities.

Enables local analysis of scientific papers including PDF parsing, mathematical formula extraction with AST generation, PyTorch code generation from methodology, and automated Markdown report generation with visualizations.

Provides calculator tools for mathematical operations, access to TypeScript SDK documentation, and meeting summary prompt templates through both stdio and SSE transports.

Enables parsing and extraction of content from various document formats (PDF, Word, Excel, PowerPoint) into Markdown format using the Niutrans document API.

Provides MCP tools to search, create, update, and comment on Jira issues, and to search, create, update, and list Confluence pages and spaces via REST API, including linking Jira issues to relevant Confluence documentation.

This MCP server connects GitLab projects and merge requests with Jira work tracking, Confluence pages, and Grafana dashboards. It provides read-only access to GitLab, Confluence, and Grafana, while Jira mutations require explicit confirmation.

Provides calculator tools for mathematical operations, document resources for accessing TypeScript SDK documentation, and prompt templates for generating structured meeting summaries. Built with FastMCP to demonstrate comprehensive MCP capabilities including tools, resources, and prompts in a single implementation.

Enables reading Yuque documents, listing knowledge base docs, and converting source content to Markdown via MCP. Supports session cookie authentication and optional Playwright rendering.

Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

Provides access to developer roadmap content from roadmap.sh, allowing users to list available roadmaps and fetch detailed Markdown content for specific career paths.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.