RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware search, DB/API/infra knowledge. 61% less tokens, 84% fewer calls, 37x faster. Cloud in beta.

100% Rust implementation of code graphRAG with blazing fast AST+FastML parsing, surrealDB backend and advanced agentic code analysis tools through MCP for efficient code agent context management

Symbol Delta Ledger (SDL-MCP) is a policy-centered context budget layer for coding agents: Symbol-graph intelligence combined with precision tools. It turns sprawling codebases into compact, high-signal context that saves tokens, speeds up workflows, and improves agent output.

Context-Engine MCP - Agentic Context Compression Suite

Meteor extracts structured context from across your systems and delivers it to power your organization's context graph and AI agents.

Shared memory for AI agents

Open Source Context infrastructure for AI agents. Auto-capture and share your agents' context everywhere.

Local AI Coding Hub: Run Claude Models Offline in 2026

Compass is a context engine that builds a knowledge graph of your organization's metadata, capturing entities, relationships, and lineage across systems and time, making it discoverable and queryable for both humans and AI agents.

Local-native Context Engine MCP server for codebase indexing, semantic retrieval, planning, and review workflows.

Cost saving Cognitive Architecture for AI Agents. Infinite Context. Perfect Recall. Zero Hallucinations.

Live context engine for AI agents: resolve verified workspace state before the context window opens. Pairs with Perseus Vault for persistent encrypted memory. Local-first, MIT. pip install perseus-ctx

Local context engine for AI coding agents. Routes tasks to relevant files, tests, rules, and skills, supports prompt caching, and builds compact context packs for Claude Code, Codex, Cursor, MCP, and more.

MCP server that provides code context and analysis for AI assistants. Extracts directory structure and code symbols using WebAssembly Tree-sitter parsers with Zero Native Dependencies.

Persistent local memory engine for OpenClaw — replaces default memory-system with a full context lifecycle: hybrid vector recall, automatic compaction, and domain-adaptive gating over LibraVDB

Universal Memory & Context Engine (MCP Server) to give Long-Term Memory to AI Agents.

Give one OpenClaw session durable memory, topic-aware continuity, and bounded token growth.

A Local Context Engine

Open-source platform for deterministic, token-aware context selection for AI agents and LLMs