"Information about Baidu, a Chinese technology company and search engine" matching MCP servers:

Enables searching documentation from GitHub repositories and web pages via MCP tools, with in-memory indexing and caching for fast retrieval.

A traceable Chinese-history MCP server that enables querying of nine classical Chinese texts (e.g., 史记, 汉书) with citations and honest status labels. It provides four tools to search events, persons, places, and qualities, all with provenance.

Enables accurate Quranic verse search through natural language queries, returning exact text with no hallucinations.

Exposes self-owned AI agent plugins as tools to Claude Code via a stdio MCP server, allowing Claude to call system info, calculator, or scribe transcriber directly.

Connects Baidu Netdisk to MCP-compatible AI clients, enabling AI to safely read selected files and generate summaries, key points, to-dos, tags, and organization suggestions.

Secure, local-first collaboration layer for AI agent teams, enabling authenticated agent-to-agent communication, shared memory with provenance, and scoped service execution through MCP.

Read-only bridge that lets DeepSeek Harness audit Baidu Netdisk directories via official MCP, blocking downloads and writes.

Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.

attendance-engine-mcp is a Model Context Protocol server that gives AI agents deterministic, fixture-backed tools for workforce attendance and wage-and-hour compliance. Built on @attendance-engine/core — a pure-function, zero-deps, 100%-covered TypeScript engine — it lets Claude, Cursor, Windsurf, or any MCP host correctly answer the questions HR/payroll teams actually ask: did this person clock i

MCP server for LinkedIn Company Page administration. Enables reading analytics, managing posts, editing page details, growing followers, and bridging personal profile for employee advocacy workflows.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables programming agents to capture errors and conversation signals, reflect on root causes, consolidate reusable skills, and retrieve relevant context for future tasks, providing a self-learning memory loop.

MCP server giving AI agents 86 tools for browser automation via Chrome DevTools Protocol, including navigation, click/fill ladders, network inspection, per-site cracks, and optional marketplace for site-specific knowledge packs.

A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.

An MCP server that brings difficulty-adaptive, multi-path reasoning to Claude Code. It implements the Actor-Critic-Planner-Reflexion (ACPR) pipeline for deep research synthesis.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

An MCP server that acts as an AI knowledge and skills hub, automatically discovering, indexing, and serving skill libraries to any MCP client with full-text search, rich metadata, and hot reload.

Local-first stdio MCP server for agent relationship-continuity state: PAD mood, affective pulse, trust, decay, and boundary signals kept beside factual memory.

Headless InDesign document composition via MCP: parse IDML templates, convert content to ICML stories, and compose complete newspaper IDML files conversationally.

Enables running the entire LinkedIn sales motion inside Claude Code, including content creation, audience warming, outreach, and booking calls.