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    A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.
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    MIT
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    The Search MCP Server enables seamless integration of network and local search capabilities in tools like Claude Desktop and Cursor, utilizing the Brave Search API for high-concurrency and asynchronous requests.
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    MIT
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    Source-verified regulatory and compliance intelligence: 10,000+ obligations across 39 pillars, each grounded in a primary legal source with a content hash. Covers the EU AI Act, GDPR, DORA, NIS2, HIPAA, Basel III and the MITRE ATT&CK/ATLAS families.
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    MIT
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    CodebaseAgent-MCP is an MCP server that uses a lightweight RAG pipeline to delegate repository analysis to a dedicated OpenAI-compatible LLM, reducing token consumption by having the primary assistant receive only the relevant findings instead of repeatedly scanning the entire codebase.
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    Apache 2.0
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    Jinni is a tool to efficiently provide Large Language Models the context of your projects. It gives a consolidated view of relevant project files complete with metadata, overcoming the limitations and inefficiencies of reading files one by one. The philosophy behind this tool is that LLM context wi
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    Apache 2.0
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    Enables comprehensive Reddit research through a three-layer architecture that discovers relevant communities, provides operation guidance, and executes multi-subreddit content fetching with proper citations. Supports searching, post fetching, comment analysis, and batch operations across multiple subreddits for thorough content analysis.
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    A black-box flight recorder for RAG retrieval inside MCP agents. Logs what chunks the model saw, scores, sources, and rankings - so you can audit, replay, and diff retrieval runs after the fact.
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    Provides tools to fetch and search news from The Verge's RSS feed, allowing users to get today's news, retrieve random articles from the past week, and search for specific keywords in recent Verge content.
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    Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.
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    MapRag is a discovery + routing layer for retrieval. It indexes RAG-capable MCP servers, enriches them with structured metadata, and helps agents (and humans) quickly find the right retrieval server for a task under constraints like citations, freshness, privacy, domain, and latency. MapRag does not do RAG itself. It helps you choose the best RAG tool/server to do the retrieval.
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    AI-powered recall over your saved bookmarks. It gives Claude semantic search, topic clusters, recent saves, and save-from-chat across the content you save from X, Reddit, LinkedIn, and the web.
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    MIT