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    An MCP-native CRM backend for AI agents, enabling customer, opportunity, note, follow-up, and pipeline health management through 15 MCP tools.
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    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.
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    MIT
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    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
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    MIT
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    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.
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    MIT
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    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.
    363
    MIT
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    Tracks macros and logs meals via plain language by exposing a local USDA food database as an MCP server.
    MIT
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    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.
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    Business Source 1.1
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    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.
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    MCP server for Tree-of-Thoughts search engine enabling deliberate problem solving with LLM agents via BFS, DFS, and beam search policies.
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    A code understanding and generation system designed for Galacean Engine that helps LLMs comprehend the engine architecture and generate high-quality engine code based on user intent.