"A server for providing information about human resources" matching MCP servers:

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

An MCP server that allows AI assistants to utilize human capabilities by sending requests to humans and receiving their responses through a Streamlit UI.

Enables LLMs to send DM messages to a human via Discord webhook when they need attention — a question, blocker, decision, or completed work — using a standardized, user-controlled format read from a local file or hosted URL.

MCP server that analyzes your writing style to generate personal voice rules, scores drafts for AI slop, and verifies authorship, enabling LLMs to write in your specific voice.

Enables AI assistants to store, score, recall, pin, sleep, wake, update, delete, and export memories with importance weighting, type-based decay, emotional valence/arousal, and dormant-memory reactivation through 14 MCP tools.

Enables controlled, human-style mouse, keyboard, and clipboard interaction with Windows applications through MCP tools for window inspection, safe activation, cursor movement, clicks, dragging, typing, scrolling, copy/cut/paste, background reading, and pause/resume safeguards.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Enables AI agents to request human actions or decisions by opening a local browser page for input, allowing the agent to pause and wait for human response.

Enables any MCP-capable harness to run queries through a real browser driving real search engines in a configurable fallback chain (Google, DuckDuckGo, Bing, Baidu, Sogou), with CAPTCHA or sign-in handoff, persistent per-engine cookies, and reported provenance for each result.

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

A public-safe research prototype for controlling AI-agent tool actions with deterministic policy, risk-based human approval, time-bound authorization and a tamper-evident audit chain.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Enables an AI agent to prepare an action, have a human approve the exact preview via a local token-protected page, and then execute it once with no replay. Provides read-only status, revocation, expiry, and verified readback so uncertain or changed actions cannot be run without explicit human approval.

A local MCP server that gathers web captures, image crops, video frames, and copy into structured evidence artifacts, letting a vision-capable agent inspect the returned media and produce evidence-backed critique with scored findings, comparisons, and quality gates. It never converts local metadata into visual judgment, so hosts must supply their own vision reasoning.

Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.

An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.

Enables AI assistants to interact with humans through GUI dialogs for text input, choices, confirmations, and information display.

Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

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.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

A fast, safe MCP server for YNAB providing read-only budget access by default, with 28 tools for budgets, transactions, categories, payees, accounts, scheduled transactions, and server-computed analytics.

MCP server adapter that exposes A-share stock data tools, prompts, and resources via FastMCP, enabling querying of stocks, K-lines, financials, sectors, and market hot spots through natural language.

Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.