"A scheduling engine powered by AI" matching MCP servers:

Enables AI assistants to recommend jobs, parse candidate profiles, compute semantic skill match scores, and filter opportunities by location through standardized MCP tools.

Enables secure execution of Python code, SQL queries, and metric fetching through MCP with ephemeral Docker sandboxing.

An MCP-native CRM backend for AI agents, enabling customer, opportunity, note, follow-up, and pipeline health management through 15 MCP tools.

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.

An agentic Retrieval-Augmented Generation (RAG) system that combines a small curated machine learning knowledge base with real-time web search capabilities, powered by the Model Context Protocol (MCP).

Enables grounded, dated research from a curated AI-knowledge repository, offering free BM25 retrieval and a research loop that combines the knowledge base, curated sources, and the open web with tiered citations.

Enables asking natural language questions about local videos, using Whisper transcription, ChromaDB vector storage, and Groq for timestamped answers via MCP.

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.

MCP server (stdio, official Python SDK) exposing a single tool: quantity_execute. Performs dimensional calculation and unit conversion with evidence. Solves silent unit errors in LLM agent chains: 20 m/s × 3 h returns 216 km.

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.

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.

Graph RAG based context management engine for coding agents

Persistent memory for AI coding assistants.

Audits AI agent skills for safety using static, semantic, adversarial, and supply-chain analysis, providing scores and risk flags. Can be run via CLI, CI, or as an MCP tool from Claude Code, Cursor, and Codex.

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.

Tracks macros and logs meals via plain language by exposing a local USDA food database as an MCP server.

Enables AI agents to manage social media posts across multiple platforms by scoring virality, generating threads, converting formats, optimizing hooks, scheduling campaigns, and validating platform limits.

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。

A local-first file intelligence engine that indexes documents, code, and email on your machine using on-device models, and exposes that memory to any AI assistant over MCP for semantic search and structured fact retrieval.