ra-h-os/apps/mcp-server-standalone

RA-H MCP Server

Connect Claude Code and Claude Desktop to your RA-H knowledge base. Direct SQLite access to an existing RA-H database.

Install

npx --yes ra-h-mcp-server@2.1.2

Run RA-H once first so the database exists, then use the MCP server from any client.

Configure Claude Code / Claude Desktop

Add to your Claude config (~/.claude.json or Claude Desktop settings):

{
  "mcpServers": {
    "ra-h": {
      "command": "npx",
      "args": ["--yes", "ra-h-mcp-server@2.1.2"]
    }
  }
}

Restart Claude. Done.

If you publish a newer MCP release and need this client to pick it up immediately, bump the pinned version here and restart Claude. Do not assume plain npx ra-h-mcp-server always refreshes instantly.

Requirements

• Node.js 18+
• An existing RA-H database at ~/Library/Application Support/RA-H/db/rah.sqlite
• Run the RA-H app at least once before using the standalone MCP server

Environment Variables

Variable	Default	Description
RAH_DB_PATH	~/Library/Application Support/RA-H/db/rah.sqlite	Database path

What to Expect

Once connected, Claude will:

• Use queryNodes for explicit node lookup when the user is trying to find a specific existing thing
• Use retrieveQueryContext when graph context is helpful for a broader task, question, or request
• Use getContext only for orientation when high-level graph state would actually help
• Treat context as optional by default — normal node creation and updates should omit context unless the user explicitly wants one; when context is intentionally provided, use context_name
• Proactively capture knowledge — when a new insight, decision, person, or reference surfaces, it proposes a specific node (title, description, optional context) so you can approve with minimal friction
• Treat edges as proposal-first — it should suggest likely relationships briefly, then create them only after you explicitly confirm
• Read skills for complex tasks — skills are editable and shared across internal + external agents
• Search before creating to avoid duplicates

Source Processing

• The standalone MCP server stores source text on the node.
• It does not split source into chunks or generate embeddings itself.
• The RA-H app owns chunking and embedding when the app is running.
• If the app is closed, writes still land in nodes.source, and the app processes them later.

Recommended Agent Memory Line

If you use external agents through this MCP server, you may add one short instruction line to your agent memory file (AGENTS.md, CLAUDE.md, etc.) as optional reinforcement:

Retrieve relevant context from RA-H before substantive work, and only suggest writing durable context back when it is clearly valuable and the user can confirm yes.

Keep the writeback prompt brief. A good pattern is:

Add "X" as a node?

RA-H should still work well without this line. The MCP tools, server instructions, skills, and docs are meant to carry the core behavior on their own.

Available Tools

Tool	Description
getContext	Get graph overview — stats, contexts, recent activity
retrieveQueryContext	Pull relevant graph context for a broader current-turn task
createNode	Create a new node
writeContext	Save one confirmed durable context node after explicit user approval
queryNodes	Search nodes by keyword
queryContexts	List or inspect contexts
getNodesById	Load nodes by ID (includes chunk + metadata)
updateNode	Update an existing node
createEdge	Create a confirmed connection between nodes
updateEdge	Update an edge explanation after explicit confirmation
queryEdge	Find edges for a node
listSkills	List available skills
readSkill	Read a skill by name
writeSkill	Create or update a skill
deleteSkill	Delete a skill
searchContentEmbeddings	Search through source content (transcripts, books, articles)
sqliteQuery	Execute read-only SQL queries (SELECT/WITH/PRAGMA)

Node Metadata Contract

Context Rule

• Creating a node never requires context.
• Normal node lookup and update flows should omit context unless the user explicitly asks for it.
• If context is intentionally provided, prefer context_name.
• Numeric context_id is treated as an internal implementation detail rather than a normal agent-facing field.

When createNode or updateNode includes metadata, prefer the canonical shape:

{
  "type": "website | youtube | pdf | tweet | note | chat | ...",
  "state": "processed | not_processed",
  "captured_method": "quick_add_note | website_extract | ...",
  "captured_by": "human | agent",
  "source_metadata": {}
}

Rules:

• source_metadata is for small factual source-specific fields only
• metadata updates merge with the existing object; they do not replace the full blob
• use captured_by = "human" for direct user creation and user-requested agent capture
• reserve captured_by = "agent" for autonomous/background creation only

Writeback Rule

• Do not ask to save every moderately useful point from the conversation.
• Only suggest a save when the context is unusually durable and valuable.
• Keep the ask terse and concrete, for example: Add "X" as a node?
• Never call writeContext unless the user has explicitly said yes.

Edge Rule

• External agents should propose likely edge candidates first.
• createEdge is the execution tool after explicit user confirmation.
• Agent-driven edge creation should always include a clear explanation sentence.

Skills

Skills are detailed instruction sets that teach agents how to work with your knowledge base. The default seeded skills are editable and shared by internal + external agents.

Skills are stored at ~/Library/Application Support/RA-H/skills/ and shared with the main app.

What's NOT Included

This is a lightweight CRUD server. Advanced features are handled by the main app:

• Embedding generation
• AI-powered edge inference
• Content extraction (URL, YouTube, PDF)
• Real-time SSE events

Testing

# Test database connection
node -e "const {initDatabase,query}=require('./services/sqlite-client');initDatabase();console.log(query('SELECT COUNT(*) as c FROM nodes')[0].c,'nodes')"

# Run the server
node index.js