obris-mcp 0.3.0

MCP server for Obris - bring your curated knowledge into any AI conversation

Obris MCP Server

An MCP server that brings your curated Obris knowledge into any AI conversation. Use the Chrome extension or upload directly to save knowledge to dedicated topics so you never start another AI chat from zero again.

Features

• List topics — Browse all your Obris topics to find the one you need
• Pull in knowledge — Retrieve saved bookmarks, highlights, and notes as context for any conversation
• Save knowledge — Capture takeaways and notes from conversations to reuse in future chats

Setup

1. Get your API key

Generate an API key from your Obris dashboard. Don't have an account? Sign up.

2. Install and configure

Claude Desktop

Add your API key to your shell profile (~/.zshrc, ~/.zprofile, or ~/.bash_profile):

export OBRIS_API_KEY=your_api_key_here

Then reload your shell:

source ~/.zshrc

Open Claude Desktop settings → Developer → Edit Config, and add the following to claude_desktop_config.json:

{
  "mcpServers": {
    "obris": {
      "command": "/full/path/to/uvx",
      "args": ["obris-mcp"],
      "env": {
        "OBRIS_API_KEY": "$OBRIS_API_KEY"
      }
    }
  }
}

Run which uvx to get the full path for "command".

Restart Claude Desktop to pick up the changes.

Claude Code

claude mcp add Obris -e OBRIS_API_KEY=$OBRIS_API_KEY --transport stdio -- uvx obris-mcp

Start a new conversation and type /mcp to verify the Obris server is connected.

Gemini CLI

gemini mcp add -e OBRIS_API_KEY=$OBRIS_API_KEY --transport stdio Obris uvx obris-mcp

Start a new Gemini session and run /mcp to verify the Obris server is connected.

Other MCP clients

See the local MCP setup guide for more options.

Tools

Tool	Description
list_topics	List all your Obris topics
get_topic_knowledge	Get saved knowledge for a specific topic
create_topic	Create a new topic to organize knowledge
add_knowledge	Save text knowledge to a topic

Examples

Example 1: Listing your topics

Prompt: "What Obris topics do I have?"

The list_topics tool is called and returns:

Topics:
- Brand Guidelines (id: 01JEXAMPLE00001)
- Marketing Images (id: 01JEXAMPLE00002)
- Shoe Dog Highlights (id: 01JEXAMPLE00003)
- Favorite Cocktails (id: 01JEXAMPLE00004)

Example 2: Getting knowledge for a topic

Prompt: "What are repeated lessons in my Shoe Dog highlights? Cite the original highlight in your answer."

The list_topics tool finds the topic, then get_topic_knowledge retrieves your saved highlights:

### On Starting Out
"I'd tell men and women in their midtwenties not to settle
for a job or a profession or even a career. Seek a calling."
---
### On Selling
"Don't tell people about your brand. Tell them about your
belief. The ones who share it will find you."

Example 3: Using knowledge to make a decision

Prompt: "Here's a cocktail menu. Based on my saved favorites, what should I order?"

The list_topics tool finds Favorite Cocktails, then get_topic_knowledge retrieves your saved recipes and tasting notes. The AI cross-references the menu with your preferences to recommend a drink you'll actually like.

Example 4: Combining multiple topics

Prompt: "Pull in my brand guidelines and marketing images. Help me design a new hero section with more of an Apple-style design approach."

The AI retrieves knowledge from both topics — your color palette, typography rules, tone of voice, and previous marketing visuals — then uses that context to generate a hero section concept that stays on-brand while incorporating the clean, minimal aesthetic you're going for.

Development

git clone https://github.com/obris-dev/obris-mcp.git
cd obris-mcp
uv sync

To run locally via Claude Desktop, add to your claude_desktop_config.json:

{
  "mcpServers": {
    "obris": {
      "command": "/full/path/to/uv",
      "args": [
        "--directory",
        "/path/to/obris-mcp/src/obris_mcp",
        "run",
        "main.py"
      ],
      "env": {
        "OBRIS_API_KEY": "$OBRIS_API_KEY"
      }
    }
  }
}

Run which uv to get the full path for "command".

Make commands

make publish            # build and publish to PyPI
make pack               # pack for MCP registry (runs version check first)
make pack-and-publish   # pack, publish to PyPI, and publish to MCP registries
make sync-version       # sync manifest.json and server.json to pyproject.toml version
make check-version      # verify all version files match and compare to live server

Privacy Policy

This server sends your Obris API key to the Obris API (api.obris.ai) to authenticate requests. It retrieves topic and knowledge data from your account. The server itself does not store any data locally or send it to any third party, however your AI client may cache or retain retrieved content according to its own data policies.

For the full privacy policy, see obris.ai/privacy.

Support

For issues or questions, contact [e-mail] or open an issue on GitHub.

License

MIT