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    Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.
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    MIT
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    MCP server + TypeScript SDK for 36 U.S. government data APIs — 188 tools. Treasury, FRED, Congress, FDA, CDC, FEC, lobbying, and more. Works with VS Code Copilot, Claude Desktop, Cursor.
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    MIT
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    MCP server with 562 tools accessing 114 government data APIs covering economic, health, education, energy, and more from federal, state, and international sources.
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    Local MCP server for generating image assets with Google Gemini (Nano Banana 2 / Pro). Supports transparent PNG/WebP output, exact resizing/cropping, up to 14 reference images, and Google Search grounding.
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    MIT
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    Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.
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    Enables AI assistants to search live jobs, view full details, save and track applications in a Kanban board, set follow-up reminders, and subscribe to job alerts—no account needed for searching.
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    MIT
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    Operations toolchain for SQLite, Cloudflare D1, and Turso. Every command is available as both a CLI and an MCP tool: inspect, diff, migrate, monitor, back up, and repair databases. 22 stdio tools, read-only by default.
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    AGPL 3.0
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    MCP server for AI-powered web research — search (Google, Brave, Serper, SearXNG), scrape any page, extract PDFs/DOCX/YouTube transcripts, academic & patent search. Single Go binary. Works with Claude, Cursor, Copilot, and any MCP client.
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    MIT
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    Single-binary Go MCP server that wraps whatsmeow to expose a personal WhatsApp account as 41 MCP tools (messaging, groups, polls, media, privacy).
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    Enables fast literal and regex search over local workspaces using a sparse n-gram index for candidate pruning, with deterministic verification against file contents.
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    MIT
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    An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.
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    MIT