"Information about backend development or backend systems" matching MCP servers:

A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.

A local-first AI backend that combines Model Context Protocol, Retrieval-Augmented Generation, and an agent runtime to answer questions from a private knowledge base.

Enables AI-powered access to authoritative design systems knowledge, including W3C standards, WCAG guidelines, and best practices from 188+ curated entries via semantic vector search.

Provides agricultural intelligence tools for pest/disease lookup, government scheme discovery, and SME knowledge retrieval via semantic search.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

A lightweight, dependency-free MCP server that answers cited queries over a Tero corpus index.json via stdio JSON-RPC 2.0, with honest refusal semantics and no silent empty results.

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.

Query 37 EU regulations — from GDPR and AI Act to DORA, MiFID II, eIDAS, Medical Device Regulation, and more — directly from Claude, Cursor, or any MCP-compatible client.

Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON

Enables AI agents to store, search, and relate typed memories with a graph-native knowledge base via the Model Context Protocol.

Enables conversion of webpages to clean markdown with content quality scoring and multi-page crawling for documentation sites. Supports Claude Code, Cursor, and Windsurf with native LangChain and LlamaIndex export formats.

Provides AI agents with database-like operations over LanceDB with automatic BGE-M3 multilingual embedding generation, enabling semantic search, CRUD operations, and safe schema migrations across structured data.

A production-minded Agentic RAG backend for informational guidance about Swiss immigration and administrative procedures, using only official Swiss government sources with evidence metadata.

An MCP server for source-grounded, page-cited evidence retrieval tailored for embedded and firmware development, returning verbatim snippets with exact citations or 'no match' to prevent fabrications.

Durable hybrid memory for AI agents. Combines vector search, BM25, temporal retrieval, and optional Memgraph knowledge graph via reciprocal rank fusion. 6 MCP tools: health, search, answer, feedback, graph_query, graph_add_triple. Self-hosted with Qdrant backend.

Provides tools for searching Agent8 game development code examples and system prompts to assist in Agent8 SDK development.

Enables AI assistants to search and ask questions about documents stored in AnythingLLM workspaces through MCP tools.

Self-hosted knowledge backend for AI agents. Provides 11 MCP tools for hybrid vector + keyword search, container-isolated knowledge bases, and 4 storage connectors (S3, Azure Blob, MinIO, filesystem). Built with .NET, runs via Docker.

Enables AI assistants to search and retrieve transcripts from the Entra.Chat podcast about Microsoft Entra ID, with timestamped YouTube links and guest information.

Mimir is Perseus's external persistent memory backend — a lightweight Rust MCP server that stores cross-session facts so agents remember what they learned last week. Zero network calls, no API keys, just SQLite + FTS5 running alongside your workspace.