"Information on Rag and Memory" matching MCP servers:

Local repo-intelligence MCP for coding agents: indexes source, symbols, call graphs, git/GitHub history, and source-bound repo memories into local database.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Enables Claude Code to perform fuzzy and semantic codebase search via a query_codebase tool.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

Structural memory for coding agents — 60% fewer tokens, refactor-safe, runs entirely on your machine.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

MCP server that provides npm package information for AI agents during TypeScript development.

A local-first MCP server that indexes code repositories and enables AI assistants to search, fetch, and navigate code using BM25 hybrid retrieval, supporting common languages and tools like Codex and ChatGPT.

MCP server that migrates SAP Module Pool programs to RAP applications interactively, using AI and SAP ADT REST APIs with human approval at each step.

Provides semantic vector search over local codebases via MCP, enabling hybrid search (dense + sparse + RRF) for any MCP client like GitHub Copilot or Claude Desktop.

Context+ is a semantic intelligence server that transforms codebases into searchable, hierarchical feature graphs using RAG, Tree-sitter AST, and spectral clustering. It provides tools for deep code discovery, blast radius analysis, and memory graph management for high-accuracy engineering tasks.

Provides coding agents with hybrid semantic and exact-identifier search across VHDL source, documentation, and general code, with cross-referencing and exact source attribution.

A fully local RAG MCP server for semantic code search and code intelligence, using AST-level chunking and hybrid search to pinpoint functions, classes, and APIs. No cloud, no API keys, zero setup.

locidx

An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.

A local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.

MCP server for semantic code indexing using vector embeddings, enabling AI agents to maintain persistent memory of codebases through natural language queries and intelligent chunking.

A stateless MCP server that gives coding agents a curated entry point to shared memory, orchestrating Hindsight (facts) and LightRAG (corpora) for automatic routing, URL ingestion, and consistency tooling.

MCP server that indexes TypeScript/React project symbols in memory, enabling agents to find definitions, references, and dependencies without reading the whole repo. Also includes a local visual dashboard with no outbound network calls.