ogham-mcp MCP Server
ogham-mcp/ogham-mcp
[](https://agentrank-ai.com/tool/ogham-mcp--ogham-mcp/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Shared memory MCP server — persistent, searchable, cross-client Claude, Opencode
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
ogham-mcp/ogham-mcp is a Python MCP server licensed under MIT. Shared memory MCP server — persistent, searchable, cross-client Claude, Opencode Topics: ai-memory, mcp, memory, pgvector, agent-memory, claude, codex, llm-tools, model-context-protocol, opencode, persistent-memory, vector-database, vector-search, postgres, llm.
Ranked #1419 out of 24846 indexed tools.
In the top 6% of all indexed tools.
Ecosystem
Score Breakdown
115 stars → growing community
Last commit 14d ago → recently updated
22/26 issues closed → responsive maintainer
7 contributors → small team
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
# Ogham MCP *Ogham* (pronounced "OH-um") -- persistent, searchable shared memory for AI coding agents. Works across clients. ## 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 theRead full README on GitHub →
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