"Jira" matching MCP servers:

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.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Jira Service Management (beta): https://www.cdata.com/download/download.aspx?sku=GKZK-V&type=beta

Provides LLM-free search tools across Confluence, JIRA, code, and project knowledge for any MCP client.

Enables an event-driven operations agent to query internal SQL, GitHub, Slack, Jira, documentation, and Kubernetes telemetry through 28 RBAC-gated MCP tools, with shared memory for playbook retrieval and incident workflows.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Enables natural-language search, page reading, deployment configuration, and build-log diagnosis over Liara cloud documentation, with a bundled corpus and no database or API key required.

DevsContext is an MCP server that provides AI coding agents with synthesized engineering context—requirements, decisions, architecture, and standards—from tools like Jira and Slack. It fetches and synthesizes relevant information on demand to help agents work on tasks correctly.

Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic search, backlink traversal). Plus Atlas, which auto-generates a cited, coverage-checked wiki from your git repos and Jira.

Provides access to Jina AI's suite of web tools including URL reading, web/image/academic search, content extraction, embeddings, and reranking capabilities. Enables AI assistants to search the web, extract content from URLs, and process information with semantic understanding.

Provides access to Jina AI's web tools including URL-to-markdown conversion, web/image/academic search, screenshot capture, document reranking, and semantic deduplication. Works with optional API key for enhanced rate limits and full feature access.

An MCP server that provides access to Jina AI's powerful web services (page reading, web search, fact checking) through Claude.

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Enables web content retrieval and semantic search capabilities through the Jina AI API. Provides tools to fetch content from URLs and perform intelligent web searches with natural language queries.

Enables AI assistants to search internal knowledge bases, create Confluence articles, file Jira tickets, and look up Okta users, with guardrails and streaming support.

Enables comprehensive academic research through the Semantic Scholar API, including paper search, author discovery, citation network analysis, and full-text access from arXiv and Wiley sources.

Enables clients to read web pages and PDFs as markdown, capture screenshots, search the web and academic sources, rerank/deduplicate content, and extract PDF elements. Supports API-key access, tool filtering, and response token limits.

Provides web content extraction, search, embedding, and reranking tools via Jina AI APIs, enabling URL-to-markdown, web search, image search, and document relevance sorting.

Provides web content extraction, search capabilities (web, arXiv, SSRN, images), semantic deduplication, and reranking through Jina AI's Reader, Embeddings, and Reranker APIs.

Provides tools for web content extraction, search, embeddings, reranking, and image processing via Jina AI APIs, enabling intelligent data retrieval and analysis.

Transforms scattered customer feedback from sources like Slack, Zoom, and JIRA into actionable product insights and AI-generated PRDs. It features over 50 tools for semantic clustering, sentiment analysis, and VOC-based prioritization to streamline product management workflows.