Skip to content

introduction.mdx

Latest commit

 

History

History
90 lines (72 loc) · 4.12 KB

introduction.mdx

File metadata and controls

90 lines (72 loc) · 4.12 KB
Raw
title Introduction
icon plug
description Connect AI assistants to your Omi data using the Model Context Protocol

What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI assistants like Claude, Cursor, and other tools interact with external data sources. Omi's MCP server gives these assistants direct access to your memories and conversations.

Semantic search across your memories and conversations Create, edit, and delete memories Browse and search full conversation transcripts

How It Works

sequenceDiagram
    participant A as AI Assistant (Claude, Cursor, etc.)
    participant M as Omi MCP Server
    participant D as Your Omi Data

    A->>M: tools/list (discover available tools)
    M-->>A: Tools allowed by the user's OAuth grant or MCP key
    A->>M: tools/call search_memories {query: "morning routine"}
    M->>D: Semantic search via Pinecone
    D-->>M: Ranked results
    M-->>A: Memories with relevance scores
Loading

Your AI assistant connects to the Omi MCP server, discovers the tools allowed by its authorization, and calls them as needed during your conversations. The hosted server supports OAuth access tokens (the default for supported ChatGPT and Claude cloud flows) and manually provisioned omi_mcp_... keys for compatible clients and local servers.

The same hosted MCP connection works across Claude, Claude Code, ChatGPT, Codex, and any compatible client. It exposes the user's Omi context as scoped tools: durable memories, conversations, people, action items, goals, chat history, daily summaries, and synced screen activity. The server's initialization instructions tell clients to retrieve task-specific evidence, confirm important claims against source records, and avoid writes unless the user clearly requested them.

When the Omi macOS app connects Claude Code or Codex, it also installs a small omi skill in that client's personal skills directory. The skill contains routing guidance only—never credentials or user data—and Omi preserves an existing user-authored skill with the same name.

Available Tools

Tool Description
get_memories List memories with optional category filtering
search_memories Semantic search across memories
create_memory Create a new memory
edit_memory Edit an existing memory
delete_memory Delete a memory
get_conversations List conversations with date/category filters
search_conversations Semantic search across conversations
get_conversation_by_id Get full conversation with transcript
get_user_profile Get Omi's cached high-level user summary
get_x_posts, search_x_posts Browse or search imported X posts and bookmarks
get_action_items, search_action_items Browse or search tasks
create_action_item, update_action_item, complete_action_item, delete_action_item Manage tasks
get_goals Retrieve active or historical goals
get_chat_messages Retrieve recent Omi chat history
get_people Retrieve recognized people and speaker samples
get_screen_activity Retrieve or summarize synced screen activity
get_daily_summaries Retrieve Omi's daily summaries

See the Tools Reference for full parameter documentation.

Comparison with Developer API

Feature MCP Developer API
Purpose AI assistant integration Direct HTTP API access
Access Read/write with AI context Read & write user data
Search Semantic search built-in Filter-based queries
Use Case Claude Desktop, Cursor, AI agents Custom apps, dashboards
Best For AI-powered workflows Batch operations, integrations
For programmatic access without AI assistants, use the [Developer API](/doc/developer/api/overview) instead.