"Multi-platform information search across productivity and knowledge tools" matching MCP servers:

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Enables AI assistants to manage tasks, projects, and analyze productivity directly in Super Productivity through real-time integration via Socket.IO bridge plugin.

Enables searching job postings across multiple boards like Indeed and LinkedIn from a single request, returning titles, companies, and salaries as JSON.

Enables MCP clients to manage Super Productivity tasks, projects, and tags via its Local REST API, including task creation, updates, starting, stopping, archiving, and reading status and Focus Mode state.

AI-powered text formatting and summarization tools for development workflows. Zero-install Streamable HTTP transport — no binary, no npm required.

A multi-domain productivity tool that currently enables job search automation, application tracking, and pipeline analysis for Career management. Future phases plan to add health tracking, workout management, and family expense monitoring capabilities.

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

A self-hosted, MIT-licensed MCP server that securely connects private documents and markdown files to LLMs. It provides a lightweight, local-first RAG infrastructure compatible with any MCP-enabled AI client or framework.

Vendor-neutral MCP server for knowledge retrieval across repositories, offering stable tools for searching, getting, and listing documents with hybrid lexical and optional semantic search.

Lets an AI assistant search, read, and write notes and sources in your self-hosted Open Notebook, with approval-gated writes and no data sent anywhere else. It bundles tools, prompts, and skills for meeting notes, decision records, weekly reviews, and source-cited research.

A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.

A flexible proxy server that aggregates multiple backend MCP servers into a single interface using STDIO or SSE transports. It supports dynamic server management via an HTTP API and utilizes namespacing to prevent tool conflicts across connected services.

Enables AI agents and MCP clients to search, retrieve, and read documents across unified knowledge sources including ShowDoc, GitHub, Gitee, ZenTao, Evernote, and Tencent Docs. It also supports connecting external MCP servers as additional knowledge sources.

Enables agents to retrieve permission-filtered document knowledge across organizations and knowledge bases, and to identify and expand business terms and typed object relationships through a unified MCP interface.

A self-hosted platform that aggregates upstream MCP servers, OpenAPI imports, and remote device connectors behind a single endpoint per profile, with per-agent scoped authorization, tool/prompt/resource catalogs, and approval-based temporary permissions. It also lets administrators distribute skills and connectors to paired devices and export client configurations.

A shared communication bus for multiple agents using NATS and MCP, enabling MCP clients to list, message, and query agents.

Enables agents to perform federated cited search and heuristic grounding across a governed versioned wiki and indexed files, inspect citation spans, and read or write scoped knowledge through HTTP or stdio MCP.

Enables multiple AI agents using MCP-compatible clients to collaborate in parallel on the same project across one or more machines, with direct messaging, a shared task board, atomic file/folder locking, presence tracking, and a live web dashboard.

An MCP server that enables AI agents to query specialized, domain-specific knowledge bases built using the LightRAG framework for enhanced retrieval-augmented generation. It allows for managing and searching knowledge graphs and vector embeddings to provide accurate, context-aware information during an AI assistant's reasoning process.

Enables AI assistants to search a shared, permission-aware PostgreSQL knowledge memory before doing work and save structured reusable solutions afterward, with multi-user visibility controls, versioning, feedback, and token-efficient retrieval across MCP clients.

Serves markdown knowledge from a git repository over MCP, providing tools to list, search, and retrieve documents.

A centralized gateway and router that integrates multiple MCP servers into a single endpoint with built-in policy enforcement and secret management. It features a Web GUI for managing tool access, audit logs, and multi-environment configurations across various sub-servers.

Enables saving and searching local notes, with tools to list notes and search backup files.

Enables deterministic calculations for AI API and subscription costs, meeting time zones, recurring schedules, and cron next-run previews, returning normalized inputs, units, assumptions, dated sources, and links to results.

Enables broad web search for current, time-sensitive information, returning short title, URL, and snippet results rather than full pages. It supports region and result-count parameters through a keyless multi-engine backend.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

MCP server for managing multiple SSH servers via AI assistants, offering tools for remote command execution, file operations, and system monitoring.

Provides a read-only MCP interface to the Santismm Knowledge Platform, offering tools to retrieve curated content on engineering, AI patterns, architectures, governance, and agent taxonomy with structured output in English, Spanish, and Portuguese.

A meta-MCP server that aggregates authoritative web search and browser research tools, providing a unified interface with a cost-efficient fetch ladder for web research.

A Model Context Protocol (MCP) server that gives AI assistants the ability to search, analyze, and extract knowledge from YouTube videos.