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"JSON File Upload, Data Vectorization, and LLM Similarity Search" matching MCP servers:

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    Upload-Post is the all-in-one social media MCP server the Model Context Protocol server for social media publishing, scheduling and analytics. Connect any MCP-compatible AI agent (Claude, Cursor, ChatGPT, Claude Desktop, n8n, and more) and publish, schedule and analyze content across 13+ social networks from one API: TikTok, Instagram, YouTube, YouTube Shorts, Instagram Reels, LinkedIn, Facebook
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    MIT
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    JSON Contracts is a local MCP server for transforming natural language into Git-controlled JSON contracts, JSON Schema validation, and structured LLM/agent outputs.
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    Apache 2.0
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    Enables fast file search on macOS using the native mdfind (Spotlight) command, with support for filtering, regex, sorting, and limiting results.
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    MIT
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    MCP server that provides AI assistants with real-time, current information about AI models from OpenAI, Anthropic, and Google, including pricing, capabilities, and context windows.
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    MIT
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    A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.
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    Windows-first MCP server for deterministic file writes with atomic create, replace, and structured edit operations, preserving encoding and newline styles.
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    Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.
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    The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.
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    Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.
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    Monitors brand mentions, citations, sentiment, competitor share of voice, and GEO performance across AI search engines.
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    A local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen, DeepSeek) alongside Anthropic and OpenAI.
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    MIT