Persistent adaptive memory for AI coding agents — MCP server with context graph, semantic search, adaptive learning, roadmap tracking, and cross-tool continuity.
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# Codevira MCP > Persistent adaptive memory for AI coding agents — learns from every session, works with every tool, remembers across every project. [](https://www.python.org/) [](LICENSE) [](https://modelcontextprotocol.io) [](CHANGELOG.md) [](CONTRIBUTING.md) **Works with:** Claude Code · Claude Desktop · Cursor · Windsurf · Google Antigravity · any MCP-compatible AI tool --- ## The Problem Every time you start a new AI coding session, your agent starts from zero. It re-reads files it has seen before. It re-discovers patterns already established. It makes decisions that contradict last week's decisions. It has no idea what phase the project is in, what's already been tried, or why certain files are off-limits. You end up spending thousands of tokens on re-discovery — every single session. **Codevira fixes this.** --- ## What It Does Codevira is a [Model Context Protocol](https://modelcontextprotocol.io) server that gives every AI agent working on your codebase a shared, persistent memory: | Capability | What It Means | |---|---| | **Zero-config setup** | Auto-detects language, source dirs, and file extensions; auto-injects IDE config — no prompts, no manual JSON editing | | **Live auto-watch** | Background file watcher auto-reindexes on every save — no manual trigger needed | | **Context graph** | Every source file has a node: role, rules, dependencies, stability, `do_not_revert` flags | | **Function-level call graph** | Knows which function calls which — callers, callees, test coverage, risk scoring | | **Semantic code search** | Natural language search across your codebase (optional — requires `[search]` extras) | | **Roadmap** | Phase-based track…
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