MCP Stdio
M

MCP Stdio

The Statsig MCP Server implements the Model Context Protocol (MCP) and supports two transmission methods, stdio and SSE, for Statsig API integration.
2 points
8.4K

What is the Statsig MCP Server?

This is a server that implements the Model Context Protocol (MCP) and is specifically designed to integrate with the Statsig API. It allows developers to interact with the Statsig service via standard input/output (stdio) or Server-Sent Events (SSE).

How to use the Statsig MCP Server?

You can use the server by configuring the mcp.json file. You can choose to use stdio transmission (default) or SSE transmission and set the API key as needed.

Use Cases

Suitable for developers who need to integrate the Statsig API into their applications, especially those who want to use the MCP protocol for model context management.

Main Features

Supports Multiple Transmission Methods
Supports two transmission methods: standard input/output (stdio) and Server-Sent Events (SSE), meeting the needs of different clients.
Easy to Integrate
Provides a simple configuration method. You can quickly integrate the Statsig API by specifying commands or URLs in the mcp.json file.
Supports API Key Configuration
Supports passing the Statsig API key via environment variables or query parameters for convenient and secure authentication.
Advantages
Supports multiple transmission methods to meet the needs of different clients.
Simple configuration for easy and quick integration into existing projects.
High compatibility and can work with mainstream MCP clients.
Limitations
Additional adaptation work may be required for clients that do not support SSE.
There may be certain security risks when passing the API key via query parameters.
Depends on the availability and stability of the Statsig API.

How to Use

Install Dependencies
First, make sure Node.js and npm are installed, then run the following commands to install dependencies and build the project.
Configure mcp.json
Configure the parameters of the Statsig MCP Server in the mcp.json file according to your needs.
Start the Server
Start the server according to the configuration and ensure it can connect to the Statsig API normally.

Usage Examples

Integration in Local Development Environment
Use the Statsig MCP Server in the local development environment to quickly test and debug the integration with the Statsig API.
Deployment in Production Environment
Deploy the Statsig MCP Server to the production environment to provide stable Statsig API integration for applications.

Frequently Asked Questions

What transmission methods does the Statsig MCP Server support?
How to pass the API key in SSE mode?
Is additional configuration required to use the Statsig MCP Server?

Related Resources

Statsig Official Documentation
The official documentation of Statsig, including API references and best practice guides.
MCP Protocol Specification
The official specification and implementation details of the Model Context Protocol (MCP).
GitHub Repository
The source code and example configurations of the Statsig MCP Server.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "Statsig": {
      "command": "node /path/to/build/index.js",
      "env": {
        "STATSIG_API_KEY": "console-YOUR-CONSOLE-KEY"
      }
    }
  }
}

{
  "mcpServers": {
    "Statsig": {
      "url": "http://localhost:3000/sse?STATSIG_API_KEY=console-<your-console-key>"
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
6.4K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
5.1K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
5.4K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
6.5K
4 points
P
Paperbanana
Python
7.9K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
6.6K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
6.7K
5 points
A
Apify MCP Server
The Apify MCP Server is a tool based on the Model Context Protocol (MCP) that allows AI assistants to extract data from websites such as social media, search engines, and e-commerce through thousands of ready-to-use crawlers, scrapers, and automation tools (Apify Actors). It supports OAuth and Skyfire proxy payment and can be integrated into MCP clients such as Claude and VS Code through HTTPS endpoints or local stdio.
TypeScript
7.7K
5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
26.0K
4.3 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
73.6K
4.3 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
36.0K
5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
21.7K
4.5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
65.4K
4.5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
32.9K
5 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
22.2K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
97.7K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase