"A server for detecting and analyzing intent" matching MCP servers:

Dry-run-first Google Ads search-term intent analyzer and negative-keyword MCP for agents.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

提供A股实时行情、历史K线、财务报表、技术指标等全方位数据查询的MCP服务器，支持盘中即时更新及批量查询。

Enables agents to estimate latent user intent, maintain belief states, and resolve ambiguous requests using entropy-based thresholding through MCP tools.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

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 that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

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

A Model Context Protocol server providing tools for querying A-share stock market data, including historical prices, financial reports, market indices, and macroeconomic indicators.

Enables autonomous agents to detect under-specified user goals, gauge reversibility and risk, and present minimal multiple-choice clarifications before committing to high-stakes execution.

Enables personal AI agents to sense ambient attention cues, compute intent probabilities, and execute reversible guarded dry-run actions without prompting. It routes routine reflexes through a fast System-1 decision layer backed by decaying episodic memory and strict safety and privacy guardrails.

Enables autonomous agents to detect under-specified, high-stakes user goals, assess their reversibility and risk, and construct minimal multiple-choice clarifications before executing. Runs as a zero-dependency MCP server or importable Python module that gates autonomous execution behind those clarifying questions.

Enables agents to translate natural-language shopping intent into aggregated multi-merchant item discovery, consolidated cross-merchant carts, and structured transaction checkout payloads. Runs as a zero-dependency, MCP-compatible engine that can also be imported directly as a Python module.

Provides 11 composable MCP tools for A-share market research, covering quotes, news, technical signals, sector performance, portfolio risk, backtesting, and paper trading, with traceable data sources and calculation basis.

MCP server providing 29 A-share analysis skills including real-time data, capital flow, limit-up tracking, technical/fundamental analysis, backtesting, risk control, and Xueqiu portfolio tracking, enabling AI agents to execute market research and strategy tasks.

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.

Serves plain-text notes that an Obsidian user has explicitly published for AI over streamable HTTP, with full-text and embedding-based search. MCP clients can read and search those notes and queue suggested edits that the user's own client applies only if the AI rules allow it.

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.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables personal AI agents to detect user attention cues, compute intent probabilities, and execute guarded dry-run actions through MCP, with low-latency reflex routing, episodic memory, and safety guardrails.

Enables agents to translate consumer shopping intent into aggregated item discovery, cross-merchant cart consolidation, and structured transaction checkout payloads across multiple merchants. It runs as a zero-dependency Python MCP server or importable module compatible with Claude Desktop, Cursor, and other work agent frameworks.

Provides comprehensive A-share (Chinese stock market) data including stock information, historical prices, financial reports, macroeconomic indicators, technical analysis, and valuation metrics through the free Baostock data source.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

An MCP-based trivia game server where AI creates rounds with two true statements and one false 'twist' about various topics, letting players guess which statement is false.

Enables AI agents to discover official public data sources, inspect their metadata and endpoint parameters, and execute live queries through a unified response envelope with a 500 ms budget.

An MCP server that scores lock-screen micro-moments from gaze, dwell, and ambient context signals to estimate impulse-shopping propensity and return personalized shopping actions. It exposes this inference over standard STDIO JSON-RPC so agents can attach zero-friction ambient intent scoring to any runtime.

Enables cross-lingual semantic intent routing and multilingual agent dispatch through a deterministic, zero-dependency MCP server, allowing AI agents to parse and route user queries across languages and delegate to appropriate agents with structured JSON output.

A memory MCP server with a dual-storage system using ChromaDB and NetworkX DiGraph, enabling efficient data management and integration with IDEs like Cursor and VSCode for enhanced research and note organization.

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.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

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.

A multi-modal user intent collection MCP server that allows AI agents to ask users questions and receive text/image replies.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

MCP server that bridges Ableton Live with AI models, enabling real-time project inspection and control such as track overview, device parameters, and audio analysis.

Enables AI-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.