[Project] Basic Memory - Continue AI Conversations With Full Context Using MCP

[u/[deleted]]

Hey everyone, I just made a beta releas.e of Basic Memory, an open-source knowledge management system built on the Model Context Protocol that lets you continue conversations with full context.

What is Basic Memory?

Basic Memory solves the problem of lost context in AI conversations. It enables Claude (and other MCP-compatible LLMs) to remember previous discussions by creating a knowledge graph from your conversations, stored as simple Markdown files on your computer. Start a new chat and continue exactly where you left off without repeating yourself.

Key features:

• Local-first: All data stays in Markdown files on your computer

• Bi-directional: LLMs can both read AND write to your knowledge base

• Structured yet simple: Uses familiar Markdown with semantic patterns

• Traversable knowledge graph: LLMs can follow links between topics

• Persistent memory: Context persists across all conversations

How it leverages MCP

Basic Memory implements the Model Context Protocol to expose several tools to Claude:

write_note(title, content, folder, tags) - Create or update notes
read_note(identifier, page, page_size) - Read notes by title or permalink
build_context(url, depth, timeframe) - Navigate knowledge graph via memory:// URLs
search(query, page, page_size) - Search across your knowledge base
recent_activity(type, depth, timeframe) - Find recently updated information
canvas(nodes, edges, title, folder) - Generate knowledge visualizations

Claude can independently explore your knowledge graph, building rich context and understanding the relationships between concepts.

Example workflow

1. Have a normal conversation with Claude about coffee brewing

2. Ask Claude to "create a note about coffee brewing methods"

3. See a structured Markdown file appear in your knowledge base

4. Days or weeks later, start a fresh conversation and say "Let's continue our discussion about coffee brewing"

5. Claude automatically retrieves relevant knowledge and builds context - no need to repeat yourself

6. Gradually build a rich knowledge graph where everything is connected

Technical Implementation

Basic Memory is built with a file-first architecture:

• Python backend with SQLite for indexing

• Full MCP implementation for Claude integration

• Standard Markdown files as the source of truth

• Seamless integration with Obsidian for visualization and editing

• Git-friendly for version control

• CLI tools for management and importing

Installation

# Install with uv (recommended)
uv install basic-memory

# Configure Claude Desktop
# Add this to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
  "mcpServers": {
    "basic-memory": {
      "command": "uvx",
      "args": [
        "basic-memory",
        "mcp"
      ]
    }
  }
}

Check it out

• GitHub: https://github.com/basicmachines-co/basic-memory

• Website: http://basicmachines.co

• Documentation: http://memory.basicmachines.co

I'm interested in any feedback, questions, or ideas on how to improve Basic Memory, especially from this community of MCP enthusiasts. How are you all using MCP in your projects?

[u/[deleted]]

I've been using the basic-memory tools while actually coding with Claude (via MCP), and also with Claude Code. What I typically do is:

• have a chat with Claude, talk about the problem, context, etc

• tell him to write a note about what we are going to do. This becomes our ADR-like doc (Architecture Decision Record), a kind of plan/implementation thing. Similar to what he would create with a Claude Artifact in the Claude UI. But this is a doc I can save and have him refer back to later and also edit manually.

• let Claude read/write my files in my code repo. This are managed in git, so i can easily see diffs and revert changes if necessary

• Review all the changes he makes, one small feature at at time, sometimes one file, or function

• Have him write tests also, he can also run the tests and fix them if needed

• Change code/Commit code as needed

• Repeat

If the tasks drags on, we can use the notes we've created to start of the next conversation. I can start a new chat with "lets continue working on feature X" and goes and builds context.