MCP ExplorerExplorer

Allora Mcp Server

@allora-networkon 10 months ago
1 MIT
FreeCommunity
AI Systems
Allora MCP Server enables AI access to prediction markets data via Model Context Protocol.

Overview

What is Allora Mcp Server

Allora MCP Server is an implementation of the Model Context Protocol (MCP) that enables AI systems to access prediction markets data from the Allora Network.

Use cases

Use cases include integrating prediction market insights into AI models, conducting market trend analysis, and developing applications that leverage real-time market predictions.

How to use

To use Allora MCP Server, clone the repository, install dependencies, set up environment variables, and run the server. You can also deploy it using Docker.

Key features

Key features include standardized access to Allora’s prediction markets data, seamless integration into AI workflows, and support for real-time data retrieval through SSE connections.

Where to use

Allora MCP Server can be used in fields such as finance, market analysis, AI research, and any application requiring access to prediction market data.

Content

Allora MCP Server

This is a Model Context Protocol (MCP) server implementation for fetching machine learning inferences from the Allora Network, providing access to Allora’s prediction markets data through the Model Context Protocol.

License: MIT

Overview

The Allora MCP server allows AI systems and applications to access Allora prediction markets data through the standardized Model Context Protocol (MCP), enabling seamless integration of prediction market data into AI workflows. This server provides direct access to Allora topics, market predictions, and inference data.

Prerequisites

Quickstart

Docker:

docker run -p 3001:3001 -e PORT=3001 -e ALLORA_API_KEY=your_api_key alloranetwork/mcp-server

# Or with environment variables in a file:
docker run -p 3001:3001 --env-file .env alloranetwork/mcp-server

docker-compose:

docker-compose up

npx:

npx @alloralabs/mcp-server

Node.js:

npm run start

API

Once the server is running, you can interact with it using any MCP client. The server exposes the following endpoints:

  • GET /sse - SSE connection endpoint for MCP communications
  • POST /messages - Message endpoint for MCP communications

Point your LLM/tooling at http://localhost:3001/sse to start using the server.

Available Tools

Tool Name Description Parameters
list_all_topics Fetch a list of all Allora topics None
get_inference_by_topic_id Fetch inference data for a specific topic topicID: number

Example Usage with Claude

When connected to Claude or other MCP-compatible AI systems, you can access Allora data with:

What topics are available in Allora?

Or get specific inference data:

What is the current prediction for BTC price in 8 hours?

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Tools

No tools

Comments

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