"Hybrid RAG System for Indexing DevOps eBooks and Online Documentation" matching MCP servers:

Enables AI agents to use a hybrid dense+sparse RAG system with tag-based long-term memory (importance, knowledge-type decay, access-frequency boost) via MCP tools for document ingestion, hybrid search, staged reranking, forgetting, and index management.

An MCP server that provides a search_docs tool with hybrid retrieval (BM25 + dense vectors) and cross-encoder reranking, backed by evaluation, prompt-injection guardrails, and OpenTelemetry tracing.

Enables question answering over technical documents (Markdown, TXT, PDF) using hybrid retrieval (vector + lexical) with cited sources and audit logging, fully locally with optional cloud fallback.

Enables hybrid retrieval-augmented generation with semantic and keyword search over documents, supporting multiple formats and providing MCP integration for Claude Desktop.

Enables natural-language and keyword search across Obsidian notes, returning reranked passages with provenance, and supports reading notes and incremental indexing.

MCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.

Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.

Enables natural language search over PDF documents using vector search, allowing MCP clients like Claude Desktop to query PDF content.

A local MCP server enabling hybrid search over documents, memory, and knowledge graphs for retrieval-augmented generation, with tools for SQLite, semantic memory, and entity-relationship queries.

A local-only codebase indexer that extracts syntax-aware chunks, creates embeddings locally, and enables semantic code search and symbol lookup via MCP.

Provides an online MCP overlay for Weavatrix Cloud and Enterprise, enabling sync, advisory refresh, and architecture contract pull with explicit confirmation.

Provides structured DevOps practices and templates (tracking, documentation, runbooks) to streamline AI-assisted PoC development, reducing CLAUDE.md bloat and ensuring consistency across projects.

Unified MCP server with 46 tools for AI expert consultations, memory service integration (semantic search, knowledge graphs), workflow automation, and code sandboxing.

Enables semantic search over local Markdown documentation using hybrid retrieval combining embeddings, keyword search, and graph traversal with automatic file watching and zero-configuration setup.

MCP server for context-aware codebase exploration using FastContext model, combining LLM-guided search with fuzzy matching to find relevant code snippets.

MCP server that indexes Obsidian notes and enables hybrid search (full-text, fuzzy, semantic) for AI assistants to find and read notes.

MCP server that enables AI assistants to manage Azure DevOps resources including Work Items, Git repositories, pipelines, and user identities.

Enables interaction with Azure DevOps through natural language in Cursor IDE. Supports work item management, pull requests, builds, releases, test management, and guided workflows for development teams, QA testers, and release management.

Automatically analyzes Python codebases and generates professional documentation including README, API docs, and setup guides.

Enables searching a knowledge base and asking grounded questions with hybrid retrieval, reranking, and cited answers.