"Managing and searching Jira ticket creation" matching MCP servers:

Enables natural language querying and semantic search over a bilingual customer support ticket dataset using SQL and embeddings.

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 a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

An MCP server that provides long-term memory and semantic search using Qdrant and OpenAI embeddings, with tools for storing, searching, and managing knowledge.

Enables Zendesk support workflows through tools for semantic ticket search, customer context retrieval, solution version assessment, and daily work summaries.

Enables querying pre-built Metabase cards for QMSCloud reporting, allowing retrieval of ticket summaries and other reports via natural language through AnythingLLM.

Enables persistent long-term memory for Claude Code across sessions, with tools for storing, searching, and managing facts, knowledge graphs, and procedural lessons.

MCP server for managing and searching multi-tenant knowledge bases backed by SQLite with FTS5, enabling AI agents to persist and retrieve content via full-text search.

Provides tools for storing, searching, and managing memories with knowledge-graph enriched context via Hydra DB's agentic memory.

Enables AI agents to interact with BeeBoo's human-in-the-loop infrastructure for managing knowledge bases, requesting human approvals, and tracking work requests. It provides tools for semantic search, authorization workflows, and task creation across platforms like Claude and Cursor.

Enables storing and querying memories in a Neo4j knowledge graph with automatic entity extraction. Supports adding episodes, searching entities and relationships, and managing graph data through natural language.

Enables interaction with Zotero libraries for searching, managing collections, items, tags, and attachments, plus optional semantic search across PDFs via local embeddings.

Enables natural language interactions with Algolia search and analytics APIs through Claude Desktop. Supports searching indices, managing data, analyzing metrics, monitoring performance, and visualizing insights across your Algolia applications.

Enables AI assistants to interact with Tencent Lexiang enterprise knowledge base for searching, reading, creating, and editing documents, managing files, and importing meeting recordings.

RAGX MCP Server enables retrieval-augmented generation with document ingestion, hybrid search, and agentic answering using Claude, exposing tools for querying, searching, and managing documents.

A local-first paper RAG server that enables searching and managing academic PDFs via MCP tools, supporting metadata enrichment and citation graphs.