Skip to main content

MCP server for Obris — bring your saved references into AI conversations

Project description

Obris MCP Server

An MCP server that brings your saved Obris references into AI conversations on Claude, ChatGPT, Gemini, and any MCP-compatible client.

Features

  • List projects — Browse all your Obris projects to find the one you need
  • Pull in references — Retrieve saved bookmarks, highlights, and notes as context for any conversation
  • Read-only — The server only reads your data; it never modifies anything in your Obris account

Setup

1. Get your API key

Generate an API key from your Obris dashboard.

2. Install and configure

Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "obris": {
      "command": "uvx",
      "args": ["obris-mcp"],
      "env": {
        "OBRIS_API_KEY": "your_api_key_here"
      }
    }
  }
}

Other MCP clients

# Install
pip install obris-mcp

# Set your API key
export OBRIS_API_KEY=your_api_key_here

# Run
obris-mcp

Tools

Tool Description
list_projects List all your Obris projects
get_project_references Get saved references for a specific project

Examples

Example 1: Listing your projects

Prompt: "What Obris projects do I have?"

The list_projects tool is called and returns:

Projects:
- Marketing Strategy (id: proj_abc123)
- Product Roadmap (id: proj_def456)
- Competitive Analysis (id: proj_ghi789)

Example 2: Getting references for a project

Prompt: "Pull in my saved references for the Marketing Strategy project."

The list_projects tool is called first to find the project ID, then get_project_references is called with project_id: "proj_abc123":

### How to Build a Content Strategy
Content strategy starts with understanding your audience...
(source: https://example.com/content-strategy)
---
### SEO Best Practices 2025
Focus on search intent rather than keyword density...
(source: https://example.com/seo-guide)

Example 3: Using references as context for a task

Prompt: "Using my Competitive Analysis references, summarize the key differentiators of our top 3 competitors."

The list_projects tool finds the Competitive Analysis project, then get_project_references retrieves all saved references. The AI uses those references as context to generate a structured summary of competitor differentiators based on your saved research.

Development

# Clone and install
git clone https://github.com/obris-dev/obris-mcp.git
cd obris-mcp
cp .env.example .env  # Add your API key

# Install with uv
uv sync

# Run locally
uv run obris-mcp

Privacy Policy

This server sends your Obris API key to the Obris API (api.obris.ai) to authenticate requests. It retrieves project and reference data from your account. No data is stored locally or sent to any third party.

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

Support

For issues or questions, contact support@obris.ai or open an issue on GitHub.

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

obris_mcp-0.1.0.tar.gz (62.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

obris_mcp-0.1.0-py3-none-any.whl (5.6 kB view details)

Uploaded Python 3

File details

Details for the file obris_mcp-0.1.0.tar.gz.

File metadata

  • Download URL: obris_mcp-0.1.0.tar.gz
  • Upload date:
  • Size: 62.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.18 {"installer":{"name":"uv","version":"0.9.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for obris_mcp-0.1.0.tar.gz
Algorithm Hash digest
SHA256 cabb79fe331355a8d92af87e053051e59328fe2ddd5f4d373f3a2cca9146b423
MD5 f87a2faca8963a9935056b04dbc643a8
BLAKE2b-256 a1e065a255d2cb9266687e10e57ce6f0cde4ee0986c1f30ecba6805ec0dba5c9

See more details on using hashes here.

File details

Details for the file obris_mcp-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: obris_mcp-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 5.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.18 {"installer":{"name":"uv","version":"0.9.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for obris_mcp-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 187c4da381bfb86cf1b0198cb662a0245ccd9e4939c9472ca4e469ce87cb6171
MD5 5f81a81df455a50d466bab41f929e1d9
BLAKE2b-256 e633e65a66bb3b941929a5901d7d8151440cc19f84eb94f70a85eeec583c25fb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page