"Slack 메시지에서 태그된 항목 조회 및 요약 방법" matching MCP servers:

Enables interaction with Slack workspaces through comprehensive channel management, messaging, user management, file uploads, and Block Kit formatting. Features secure credential storage via macOS Keychain and supports all major Slack operations including reactions and workspace information.

Provides read-only MCP tools to search and retrieve articles from the AI Architect Korean tech blog, covering topics like MCP, AI agents, and enterprise architecture.

An MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.

re-backlog idea management with decision tracking, signal aggregation, and RICE scoring. Captures product feedback from Slack, Teams, Discord, and GitHub

A server implementing Model Context Protocol that enables AI assistants to interact with Slack API through a standardized interface, providing tools for messaging, channel management, user information retrieval, and more.

Provides a compiled knowledge substrate, extracting atomic claims from an append-only capture log and querying a bitemporal claim graph over MCP. Read-only by default, with opt-in writes for trusted sources.

Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.

Provides an MCP protocol interface for interacting with Elasticsearch 7.x databases, supporting comprehensive search functionality including aggregations, highlighting, and sorting.

缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台，致力于通过代理AI技术减少人力成本，高效高精度为用户提供分钟级接入的内容风控解决方案，破解安全威胁，提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel

Enables querying and managing personal/team internal knowledge from sources like Slack, Gmail, and Drive through semantic search and retrieval.

Search your company's connected knowledge from any AI tool that speaks the Model Context Protocol. Supports querying across sources like Drive, SharePoint, Confluence, Slack, and Notion with permission filtering.

Enables programming agents to retrieve internal R&D documentation with traceable, reproducible evidence through the MCP protocol, supporting multi-corpus routing and access control.

Enables structured team communication for Claude Code agents through Slack-like channels and direct messages. Supports project isolation, subscription management, and agent notes for sophisticated multi-agent collaboration workflows.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

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.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Exposes your Google Drive, Slack, GitHub, and Railway to MCP clients with semantic search, per-user permissions, and optional OAuth, allowing natural-language access to your private data and infrastructure.

Self-improving documentation engine that ingests Slack and GitHub PRs to detect knowledge gaps and improve documentation automatically.

An MCP server that provides a unified hybrid-search interface over Slack, wikis, code, and databases, enabling agents and humans to query scattered knowledge with exact and semantic search.

Enables semantic search and retrieval of information from personal and team knowledge repositories including Slack, Gmail, Dropbox, Google Drive, and uploaded files. Allows storing new information for future recall through AI-powered search.