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Engram MCP Server - Git-Backed Memory Dashboard

Engram is a self-hosted MCP server + dashboard that gives AI agents shared memory over a git-backed folder of markdown files. What differentiates it from other memory servers: search is authoritative - it always returns the latest committed version, not a stale embedding. The dashboard provides human visibility into what agents are remembering.

Source: awesome-mcp-servers PR #9807 (discovered July 19, 2026) Category: Knowledge & Memory Author: rwnalds Repo: https://github.com/rwnalds/engram Status: Active

Why This Matters

Most vector-based memory solutions have a fundamental problem: the embedding and the source document drift apart. Engram solves this by making the source of truth a git repository of markdown files - every write is a commit, every read is from HEAD. The dashboard lets humans audit what agents are writing, edit memories directly, and roll back bad writes via git.

Installation

# Clone and run via Docker
git clone https://github.com/rwnalds/engram
cd engram
docker-compose up -d

# Or run directly
npm install -g engram-mcp
npx engram-mcp

Claude Desktop / Hermes Configuration

{
  "mcpServers": {
    "engram": {
      "command": "npx",
      "args": ["engram-mcp"],
      "env": {
        "ENGRAM_REPO_PATH": "~/.engram/memory",
        "ENGRAM_PORT": "3001"
      }
    }
  }
}

Key Tools

Tool Description
write_memory Commit a new memory as a markdown file
search_memory Authoritative search - always returns HEAD version
edit_memory Modify an existing memory (creates a new commit)
list_memories Browse all stored memories with metadata
get_history View git log for a specific memory file

Dashboard

Engram includes a web dashboard at http://localhost:3001 where humans can: - Browse all agent-written memories - Edit or delete entries manually - View git history and diffs - Roll back to any previous version

CorpusIQ Relevance

Engram's git-backed approach is philosophically aligned with how CorpusIQ already operates (GBrain's markdown vault, git-tracked docs). Could serve as a lighter alternative to GBrain for teams that want agent memory without the full knowledge graph infrastructure.

See Also

  • [[sweeps/sweep-july19-2026]]
  • Linksee Memory
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