Enables AI assistants to query and retrieve information from Amazon Bedrock Knowledge Base using the Retrieve API, returning search results with content, location, and relevance scores.
Enables management of Amazon Bedrock Knowledge Bases including creation, data source configuration, document ingestion, and RAG (Retrieval-Augmented Generation) queries with support for multiple embedding models and custom parsing/chunking strategies.
Local RAG knowledge base for Qwen Code, enabling document indexing and semantic search via MCP tools. Supports metadata filtering and document retrieval without external dependencies.
A local-first knowledge base server that enables AI clients to store, retrieve, and manage documents using semantic search. Provides privacy-focused, offline-capable memory for AI assistants with tools for ingesting, querying, updating, and deleting knowledge.
An MCP server that enables users to retrieve information from AWS Knowledge Bases using RAG (Retrieval-Augmented Generation) via Bedrock Agent Runtime.
Enables governed, audit-traced AI access to a curated knowledge base through the Model Context Protocol, with OAuth 2.1 authentication and policy enforcement for secure, compliant queries.
A local-first MCP server for building and querying PDF knowledge bases. It indexes PDFs into DuckDB and exposes evidence-grounded retrieval tools to separate corpus-backed answers from independent reasoning.
Enables semantic and keyword search of Ceph documentation with version-aware, component-scoped indices, supporting command lookup and code example retrieval.
Enables semantic search over a local knowledge base using MCP tools, allowing AI clients to retrieve relevant document chunks via the search_knowledge tool.
Enables searching and retrieving Claude Code conversation history via hybrid semantic and keyword search, allowing the agent to access its own past interactions.
A local-first knowledge base for LLM coding agents that indexes repository documentation, concept ontology, and build targets into Qdrant and exposes retrieval as MCP tools (search, get, list sources, reindex).
HTTP MCP gateway for a learning corpus that enables remote agents to perform semantic search, graph queries, and routing via Pinecone and Neo4j without direct database credentials.