Bitcoin

Provides an LLM interface for Bitcoin prices via CoinGecko data through an MCP bridge.

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6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "kirtiapte-bitcoin-mcp-server": {
      "command": "java",
      "args": [
        "-jar",
        "/path/to/bitcoinn-mcp-server/target/bitcoinn-mcp-server-0.0.1-SNAPSHOT.jar"
      ]
    }
  }
}

You can run this MCP Server to provide an LLM-friendly interface for tracking Bitcoin prices via CoinGecko APIs. It exposes a lightweight, interoperable capability so your AI tools can query price data and incorporate real-time market signals into conversations.

How to use

You will connect an MCP client to the Bitcoin MCP Server to request current or historical Bitcoin price data. Use the MCP interface to ask for price updates, price changes over a period, or price movement summaries. The server acts as a bridge between your AI model and CoinGecko data, returning structured results that your model can interpret and present to users.

How to install

Prerequisites: ensure you have a Java runtime and the Maven wrapper available in your project workspace.

Build the server to produce the executable jar:

./mvnw clean package

Run the server using the generated jar. Replace the path with the actual location of the built artifact on your system.

java -jar /path/to/bitcoinn-mcp-server/target/bitcoinn-mcp-server-0.0.1-SNAPSHOT.jar

Configure your MCP client with a server entry that points to this local process. Example configuration (adjust the jar path to your environment):

{
  "mcpServers": {
     "bitcoin-mcp-server": {
      "command": "java",
      "args": [
        "-jar",
        "/path/to/bitcoinn-mcp-server/target/bitcoinn-mcp-server-0.0.1-SNAPSHOT.jar"
      ]
    },
}

Deploy on to Cloud Foundry

You can deploy the server to Cloud Foundry to expose it as an MCP endpoint your AI tools can connect to.

cf push -f manifest.yml

If you need to expose the MCP server URL to your tooling, create a user-provided service and bind it to your app.

cf cups bitcoin-mcp-server -p '{"mcpServiceURL":"https://your-bitcoin-mcp-server.example.com"}'

Bind the MCP service to your application and restart to register the MCP server with your agent.

cf bind-service ai-tool-chat bitcoin-mcp-server

cf restart ai-tool-chat