mcp-server-kalshi
A MCP server to interact with Kalshi prediction markets
1
Github Watches
0
Github Forks
1
Github Stars
MCP Server Kalshi
This is an MCP server for the Kalshi REST API
Configuration
Claud Desktop
Setting up with UVX
"mcpServers": {
  "kalshi": {
    "command": "uvx",
    "args": ["mcp-server-kalshi"],
    "env": {
        "KALSHI_PRIVATE_KEY_PATH": "PATH TO YOUR RSA KEY FILE",
        "KALSHI_API_KEY": "<YOUR KALSHI API KEY>",
        "BASE_URL": "https://api.elections.kalshi.com"
    }
  }
}
Setting up with Docker
- 
Build the container from root directory
docker build -t mcp-server-kalshi . - 
Configure client to run the container (ensure the bind command gives the container access to your rsa key files)
 
"mcpServers": {
  "kalshi": {
    "command": "docker",
    "args": ["run", "--rm", "-i", "--mount", "type=bind,src=/Users/username,dst=/Users/username", "-e", "KALSHI_PRIVATE_KEY_PATH", "-e", "KALSHI_API_KEY","-e", "BASE_URL", "mcp-server-kalshi"],
    "env": {
        "KALSHI_PRIVATE_KEY_PATH": "PATH TO YOUR RSA KEY FILE",
        "KALSHI_API_KEY": "<YOUR KALSHI API KEY>",
        "BASE_URL": "https://api.elections.kalshi.com"
    }
  }
}
Local Development
- 
Create a
.envfile in the root directory with the following variables- 
BASE_URLThe kalshi API URL - 
KALSHI_API_KEYThe API key for the corresponding environment - 
KALSHI_PRIVATE_KEY_PATHA filepath to a file containing your Kalshi RSA private key 
 - 
 - 
Install deps via
uv pip install -e .Dev deps can be installed withuv pip install -e .[dev] - 
Run with
uv run start 
Getting Kalshi API Creds
To get Kalshi API creds, follow the instrictions here
Getting a Test Account
You may want to run the server against a kalshi demo account. To get an account, follow the instructions here
Then, set BASE_URL=https://demo-api.kalshi.co for this MCP server and update your KALSHI_API_KEY and KALSHI_PRIVATE_KEY_PATH to point towards credentials generated in the testing environment
UVX
To run in MCP inspector
npx @modelcontextprotocol/inspector uv --directory /path/to/your/mcp-server-kalshi run start
To run in claud desktop, update your MCP config to:
{
    "mcpServers": {
        "kalshi": {
            "command": "uv",
            "args": [ 
            "--directory",
            "/<path to repo root directory>",
            "run",
            "start"
            ],
            "env": {
                "KALSHI_PRIVATE_KEY_PATH": "PATH TO YOUR RSA KEY FILE",
                "KALSHI_API_KEY": "<YOUR KALSHI API KEY>",
                "BASE_URL": "https://api.elections.kalshi.com"
            }
        }
    }
}
                                相关推荐
I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.
I find academic articles and books for research and literature reviews.
Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.
Confidential guide on numerology and astrology, based of GG33 Public information
Advanced software engineer GPT that excels through nailing the basics.
Emulating Dr. Jordan B. Peterson's style in providing life advice and insights.
Your go-to expert in the Rust ecosystem, specializing in precise code interpretation, up-to-date crate version checking, and in-depth source code analysis. I offer accurate, context-aware insights for all your Rust programming questions.
Converts Figma frames into front-end code for various mobile frameworks.
Discover the most comprehensive and up-to-date collection of MCP servers in the market. This repository serves as a centralized hub, offering an extensive catalog of open-source and proprietary MCP servers, complete with features, documentation links, and contributors.
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.
Micropython I2C-based manipulation of the MCP series GPIO expander, derived from Adafruit_MCP230xx
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
🧑🚀 全世界最好的LLM资料总结(Agent框架、辅助编程、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型) | Summary of the world's best LLM resources.
Mirror ofhttps://github.com/agentience/practices_mcp_server
Reviews
user_YHkKBB8K
I've been using the QGISMCP - QGIS Model Context Protocol Integration by jjsantos01 and it's been transformative for my GIS projects. The seamless integration with QGIS enhances workflow efficiency and the intuitive interface makes complex data management straightforward. Highly recommend checking it out at https://mcp.so/server/qgis_mcp/jjsantos01!