CrowdCent MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@CrowdCent MCP Serverdownload the training data for the current challenge and show me the first few rows"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
crowdcent-mcp has moved
The CrowdCent MCP server now ships inside the
crowdcent-challenge
package as an optional extra. One config line replaces this repository, no
clone or absolute paths needed:
{
"mcpServers": {
"crowdcent": {
"command": "uvx",
"args": ["--from", "crowdcent-challenge[mcp]", "crowdcent-mcp"],
"env": {"CROWDCENT_API_KEY": "your_api_key_here"}
}
}
}Prefer nothing installed at all? Connect the hosted server at
https://mcp.crowdcent.com/mcp with your API key as a bearer token.
Migrating from this repository
If your mcp.json points at a local clone (uv run --directory /path/to/crowdcent-mcp server.py), replace that server entry with the
uvx block above. That is the whole migration.
One tool changed: switch_challenge is gone. Challenge-scoped tools now
take an optional challenge_slug argument instead (defaulting to
hyperliquid-ranking), and new simulation tools let your assistant
backtest portfolio constructions on the meta-model.
Docs: docs.crowdcent.com/ai-agents-mcp
The original source remains available in this repository's git history.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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