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High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

openlore provides persistent architectural memory for AI coding agents by turning codebases into queryable knowledge graphs featuring static analysis, living specs, automated drift detection, and graph-native MCP tools to eliminate context decay and drastically slash orientation token costs.

A unified Zero-Trust MCP server that gives IDE agents local semantic codebase search, isolated episodic project memory, and hallucination-free framework RAG.

Persistent memory and codebase intelligence for AI coding agents, indexes symbols, tracks sessions, and exposes structured project knowledge through an MCP server so agents stop re-reading files and start building on what they already know.

🏛️ Memory System for AI Coding Tools - Never explain your codebase again. MCP server with perfect project isolation, 95.8% context accuracy, and the Four Pillars Framework.

Local codebase memory, auto-generated wiki, and interactive architecture dashboard for Claude Code and MCP. AST indexing, call graphs, hybrid search, topology analysis. 0 tool calls, 3-8x fewer tokens, everything stays on your machine.

Stop re-explaining your codebase to AI. Infinite speed memory + code graph for Claude Code & Codex CLI. 17 MCP tools, subagent protocol, hybrid search, TUI dashboard, crash recovery. Save 80-200K+ tokens/session.

A persistent, multi-agent Model Context Protocol (MCP) server. Continuum gives AI coding agents — Claude Code, OpenCode, Codex, Gemini CLI — a shared, live view of a codebase and a memory that survives across agents and sessions.

Local MCP server that gives AI coding agents persistent, searchable memory of your codebase

CodeGraph builds a semantic graph of your codebase — functions, classes, imports, call chains — and exposes it through 42 MCP tools, 38 languages, a VS Code extension, and a persistent memory layer. AI agents get structured code understanding instead of grepping through files.