ogham-mcp

# Ogham MCP *Ogham* (pronounced "OH-um") -- persistent, searchable shared memory for AI coding agents. Works across clients. [](https://opensource.org/licenses/MIT) [](https://github.com/ogham-mcp/ogham-mcp/pkgs/container/ogham-mcp) [](https://python.org) [](https://pypi.org/project/ogham-mcp/) ## What it is AI coding agents forget everything between sessions. Switch from Claude Code to Cursor to Kiro to OpenCode and the context is gone -- decisions, gotchas, the shape of your codebase -- so you repeat yourself, re-explain, and re-debug the same issues. Ogham gives your agents one shared memory that persists across sessions and clients. It is a **retrieval engine**: it stores what matters and finds it again, and your LLM reads the results. The retrieval is **structured** -- hybrid search plus a typed-edge graph, not just vector similarity. That is what lets it answer questions whose answer is a *path between two facts*, the case where plain vector RAG falls down. ## Quick start ```bash uvx --from ogham-mcp ogham init ``` `ogham init` runs a setup wizard: it connects your database, picks an embedding provider, migrates the schema, and writes the MCP client config (Claude Code, Cursor, VS Code, and others). For Claude Code it runs `claude mcp add` for you; for other clients it prints the snippet to copy. **You need a database first** -- a free [Supabase](https://supabase.com) project or a [Neon](https://neon.tech) database. On Neon or self-hosted Postgres, install the postgres extra so the driver is available: ```bash uvx --from 'ogham-mcp[postgres]' ogham init ``` Then tell your agent to remember something and ask about it later -- from the same client or a different one. They share the databa…