"Integrating Confluence with AI Features like Search and Summarization" matching MCP servers:

Enables retrieval of relevant context from Confluence pages using RAG and ChromaDB, integrating with code assistants like GitHub Copilot to enhance documentation queries.

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.

An MCP server that connects AI assistants to Confluence, enabling search and fetch of pages in real time.

Bridges Confluence Wiki with Large Language Models, allowing them to search, read, and explore content through automated HTML-to-Markdown conversion. It supports both local stdio and containerized HTTP/SSE transport modes for flexible deployment.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

A Model Context Protocol (MCP) server that connects AI agents to Confluence Cloud. Agents can search, read, create, and update Confluence content — pages, comments, links, images, and labels.

Syncs Confluence spaces to local files for efficient editing by coding agents, with tools for reading, writing, searching, and managing Confluence pages and attachments.

Provides tools for AI agents to interact with Atlassian Confluence, enabling search, space listing, and CRUD operations on pages via natural language.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Enables Claude to receive physical touch events from a phone via the PWA and respond with text, haptic vibrations, and expression changes, giving an AI companion embodied presence through touch.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Converts Markdown files to Atlassian Document Format and publishes them to Confluence, with support for rendering Mermaid diagrams as PNG attachments.

A self-hosted, MCP-native web-search backend for AI agents that provides meta-search, clean extraction, RAG with citations, and GitHub project selection.

A Node.js MCP server providing browser search and web page access capabilities, including Google search, intelligent web analysis, and LLM-powered summarization.

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.

Allows MCP clients to create, validate, preview, and submit product showcases on Build with AK, with support for local stdio and remote HTTP transports.

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