"Slack Bot with RAG Document Retrieval and Automated Response System" matching MCP servers:

Enables AI coding assistants to query private academic paper collections via standard MCP tools, with hybrid retrieval, reranking, and inline citations.

Provides retrieval and analysis tools for a quantitative-finance research library, enabling whole-passage answers with verifiable citations, citation checking, entity graph exploration, and corpus inspection.

AI-powered research assistant MCP server for searching academic papers and answering research questions with DOI citations.

Enables Claude to search a local hybrid retrieval index of research papers and ingest new PDFs, providing research-paper memory queryable directly through natural language.

Local document intelligence for AI agents — extract text, detect tables, read metadata, analyze structure, search keywords, and detect language from PDF and DOCX files. No cloud API required, no API key needed.

Document Comparison AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Universal MCP server for extracting text from various document formats including PDF, Excel, Word, CSV, and more, with support for streaming, limits, and markdown conversion.

Enables creation and management of academic-paper knowledge bases from PDFs, including ingestion, semantic search with reranking, and document-level retrieval via MCP tools.

MCP server that integrates a 1200-paper RAG database with six tools to support research workflows across stages like hypothesis, experiment, statistics, and writing. It routes requests to specialized skills and real-time frontier searches to provide evidence-grounded research mentoring.

A production-quality multi-agent research system with an arXiv MCP server and LangGraph-based research agents, providing search, details, and cached summaries via SQLite.

Exposes hybrid document retrieval and evaluation tools from retrieval-lab via MCP, including search_documents, corpus_info, run_evaluation, and search_my_repos, with wire-level conformance tests.

A local MCP server for evidence-safe academic citation workflows, including verified-reference retrieval, Zotero duplicate detection and import, and Word export via Pandoc with zotero.lua.

Enables users to collect, search, and retrieve product feedback and full conversation threads directly from Slack channels. It supports filtering messages by specific stakeholders and time ranges to facilitate efficient feedback analysis.

Parses various document formats (PDF, Word, Excel, PowerPoint) into Markdown content using NiuTrans API, enabling extraction and reading of document text through natural language interactions.

Enables users to connect their own account to AI clients to list notebooks and sources, fetch complete indexed source text and summaries, and ask grounded questions that return citation-to-source mappings, without creating, renaming, uploading, sharing, or deleting content.

Enables discovering and independently validating scholarly metadata from extracted research text using Crossref, OpenAlex, DataCite, and optional read-only Zotero checks, returning ranked and verified reference candidates.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

A local-first paper RAG server that enables searching and managing academic PDFs via MCP tools, supporting metadata enrichment and citation graphs.

Enables AI agents and MCP clients to heuristically parse multi-column document dumps, aligned spacing, and CSV/TSV input, converting them into clean GitHub Flavored Markdown tables and typed JSON. Runs fully offline on the Python standard library with zero external dependencies, returning deterministic results without LLM round-trips.

Enables AI agents and MCP clients to convert ASCII/OCR text dumps, aligned spacing, and CSV/TSV data into clean GitHub Flavored Markdown tables and typed JSON deterministically.