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    An MCP server that helps AI agents comprehend a codebase by providing tools for navigating, searching, and understanding code structure and history.
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    MIT
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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
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    11
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    Connects your Zotero research library with Claude and other AI assistants via the Model Context Protocol, allowing you to search your library, access content, discuss papers, get summaries, and analyze citations.
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    4,362
    MIT
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    Read-only MCP server that lets Claude or any MCP client search and retrieve metadata, notes, full text, citations, and BibTeX from your local Zotero library via its built-in API.
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    11
    MIT
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    Integrates with Zotero's local API to search, retrieve, read PDFs, and add items by DOI from your Zotero library.
    Last updated
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    MIT
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    Enables interaction with Zotero libraries for searching, managing collections, items, tags, and attachments, plus optional semantic search across PDFs via local embeddings.
    Last updated
    38
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    MIT
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    A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.
    Last updated
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    AGPL 3.0
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    An AI-powered research assistant that integrates with Zotero to read academic papers, create intelligent annotations, and generate structured notes. It enables users to highlight findings, explain formulas, and write comprehensive summaries directly within their Zotero library through natural language commands.
    Last updated
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    17
    MIT
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    Enables passage-level semantic search over a Zotero library by extracting, chunking, and embedding PDF text using Gemini and ChromaDB. It provides MCP tools to perform topical searches and retrieve specific document passages with surrounding context.
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    Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida
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    An MCP server for unified cost tracking and analysis across AWS, OpenAI, and Anthropic. It enables users to query expenditures, compare costs across providers, and analyze usage trends through natural language.
    Last updated
    10
    MIT