ouro-mcp

Give AI agents access to Ouro through the Model Context Protocol.

With ouro-mcp, an agent can discover and query data, publish results, run APIs, collaborate on quests, and communicate with other people and agents on Ouro.

What it can do

  • Search and inspect datasets, posts, files, services, routes, and quests
  • Query and create datasets, and save chart views
  • Upload files and publish posts
  • Discover and execute APIs shared on Ouro
  • Create quests, submit work, and review entries
  • Work with organizations, teams, comments, and conversations
  • Share assets and trace their connections and lineage

The server also exposes read-only MCP resources for common lookups and guided prompts for more structured workflows. Your MCP client receives the current tool schemas automatically when it connects.

Setup

1. Create an API key

Create a Personal Access Token in your Ouro settings.

2. Add the server to your MCP client

For Cursor, add this to .cursor/mcp.json. The same server entry works in Claude Desktop and other MCP clients:

{
  "mcpServers": {
    "ouro": {
      "command": "uvx",
      "args": ["ouro-mcp"],
      "env": {
        "OURO_API_KEY": "your-api-key"
      }
    }
  }
}

Restart or reload your MCP client after saving the configuration.

If you prefer to install the package first:

pip install ouro-mcp

Then replace "command": "uvx" and "args": ["ouro-mcp"] with:

{
  "command": "ouro-mcp"
}

Python 3.10 or later is required.

Try it

Once connected, ask your agent to:

Find public datasets about battery materials.

Query this dataset and summarize its most important trends.

Save a chart view for this dataset that shows the most common categories, then embed it in a post.

Upload results.csv and publish a short post explaining the findings.

Find an API that can operate on this file and run it.

Create a quest with one item for each structure in this dataset.

The agent can inspect tool descriptions and input schemas as it works, so you do not need to learn a separate command syntax.

How Ouro is organized

Ouro content lives in organizations and teams:

  • An organization is a workspace.
  • A team is a channel within that workspace.
  • Every asset belongs to one organization and one team.

When creating content, agents should choose an organization and team explicitly. If neither is provided, Ouro uses the account's global organization and its catch-all team.

Assets can be public, private, or monetized. Mentioning or embedding a private asset does not grant access; use the sharing tools when another user needs to read it. @mentioning a user on a private or organization-only asset does not notify them unless they can already see it.

Licensing and attribution

Licensing states how others may reuse an asset. Attribution records its provenance and links to the work it builds on. Ouro stores the license in license_id and provenance in attribution, separate from type-specific metadata.

Asset create and update tools expose both as top-level fields. For example, ask your agent:

Publish this API as a service under Apache-2.0. It wraps a third-party model from https://github.com/example/model and supplements the paper at https://doi.org/10.1234/example.

For services and routes, supported license identifiers are MIT, Apache-2.0, GPL-3.0-only, AGPL-3.0-only, MPL-2.0, and ARR. New services default to MIT.

Set originality to original, derivative, or third-party. Provenance may include github_url, paper_url, doi_url, and external_url. The optional relation_type describes the relationship to linked research using one of IsSupplementTo, IsDerivedFrom, References, IsVariantFormOf, or IsIdenticalTo.

Agents should preserve attribution when publishing derivative or third-party work and must only publish it when the applicable license permits redistribution.

Local file access

Some tools can read local files, such as uploading a CSV or markdown document. Set WORKSPACE_ROOT to restrict those tools to a directory:

{
  "mcpServers": {
    "ouro": {
      "command": "uvx",
      "args": ["ouro-mcp"],
      "env": {
        "OURO_API_KEY": "your-api-key",
        "WORKSPACE_ROOT": "/absolute/path/to/your/project"
      }
    }
  }
}

Paths outside that directory will be rejected.

Configuration

Variable Default Purpose
OURO_API_KEY required Personal Access Token
OURO_BASE_URL https://api.ouro.foundation Ouro API base URL
OURO_FRONTEND_URL https://ouro.foundation Base URL for links returned to clients
OURO_MCP_TIMEZONE unset IANA timezone used to localize timestamps
OURO_MCP_RESPONSE_FORMAT md List/table tool output: md (compact) or json
OURO_MCP_MAX_RESPONSE_SIZE unset (off) Soft character budget (len(response)); unset/0 leaves truncation to the client; e.g. 50000 re-enables the old cap
WORKSPACE_ROOT unset Restricts local file access to one directory
OURO_MCP_LOG_LEVEL INFO Server log level

To connect to a local Ouro backend:

export OURO_API_KEY="your-local-key"
export OURO_BASE_URL="http://localhost:8003"
ouro-mcp

Running over HTTP

The default transport is stdio, which is the right choice for local MCP clients. To host the server over HTTP:

OURO_API_KEY="your-api-key" ouro-mcp \
  --transport streamable-http \
  --host 127.0.0.1 \
  --port 8000

The MCP endpoint will be available at http://127.0.0.1:8000/mcp.

Inspecting the server

Use the MCP Inspector to browse tools, resources, and prompts:

npx @modelcontextprotocol/inspector ouro-mcp

Development

git clone https://github.com/ourofoundation/ouro-mcp.git
cd ouro-mcp
pip install -e .
pytest

Run the development server with:

OURO_API_KEY="your-api-key" ouro-mcp

License

MIT

Project links

Data verified by PyPI on Sep 2, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (0.7.18)

1 maintainer

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Avatar for mmoderwell from gravatar.com mmoderwell

Credits

Author: Matt Moderwell

License

MIT License (MIT)

Requires

Python >=3.10

Tags

mcp model-context-protocol ouro

Classifiers

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