"Using an MCP server with Atlassian JIRA to extract ticket descriptions" matching MCP servers:

It allows AI agents to perform hybrid searches across historical issue tracker data (JIRA and MantisBT) to discover past problems and their corresponding resolutions. This capability helps automate the discovery of suitable precedents for new support inquiries.

Model Context Protocol (MCP) server for Atlassian Cloud products (Confluence and Jira). This integration is designed specifically for Atlassian Cloud instances and does not support Atlassian Server or Data Center deployments.

An AI-powered support ticket management system that lets users retrieve, search, and update support tickets using natural language.

MCP server for Atlassian Confluence and Jira, enabling AI assistants to search, create, and update issues and pages via natural language.

Enables AI assistants to search and retrieve data from Jira and Confluence directly within MCP-compatible IDEs. It provides tools for managing Jira tickets and Confluence pages using OAuth 2.0 authentication and Hexagonal Architecture.

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

Enables small local models to persist and retrieve long-term user facts through remember and recall tools, using SQLite FTS5 keyword search for lightweight memory without external vector databases or heavy VRAM.

A read-only MCP server that enables querying and searching Atlassian Confluence pages and Jira issues through their REST APIs. Supports retrieving content by ID or URL, searching using CQL/JQL, and listing spaces and projects.

MCP server for Atlassian Jira running serverless on AWS, enabling JQL search and issue retrieval via MCP.

Enables MCP-capable AI assistants to search and retrieve past Jira issues, resolutions, and recurring topics from a fully local embedded knowledge base using hybrid semantic and keyword search.

Connects Jira projects to AI assistants, enabling natural language queries to view, search, and filter stories with real-time access to descriptions, comments, status, and metadata without leaving your development environment.

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A Model Context Protocol server that enables AI assistants like Claude to access and search Atlassian Confluence content, allowing integration with your organization's knowledge base.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

MCP server that connects AI assistants to your Jira site, supporting PAT or SSO authentication for search, read, create, update, and delete operations on issues.

An MCP server that enables communication with Jira, allowing users to perform operations like getting, searching, creating, and editing issues through natural language interaction.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables users to discover jobs by target titles and countries, rank job descriptions by skill coverage across all imported resumes, generate tailored ATS-ready resumes and cover letters, and fill and submit requested application batches through a signed-in AI host with browser access.

A clean, reliable Model Context Protocol server for Jira integration, enabling issue management, search, and more via natural language.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.

An AI-friendly JIRA integration server using the Model Context Protocol, providing semantic tools for searching and interacting with JIRA issues without requiring JQL knowledge.

Enables Claude to translate natural-language business questions into safe, read-only SQL queries by exposing tools for listing tables, inspecting schemas, and executing row-capped SELECT statements against PostgreSQL.

Enables users to interact with PostgreSQL databases through natural language, with GitHub OAuth authentication and role-based access control.

A secure database query service built on FastMCP framework that allows users to query MySQL databases using natural language, with comprehensive permission management and security controls.

Enables Claude to interact with Jira through JQL (Jira Query Language) queries using the Model Control Protocol, allowing natural language access to Jira issue tracking and project management.

Enables resolving the likely employer behind Gmail, Outlook, iCloud, Yahoo, and other free-mail signups by checking public Gravatar profiles, signed GitHub commits, and LinkedIn results. It returns the person’s name, employer, employer domain, confidence score, and evidence URLs.