MCP Bridge Api
M

MCP Bridge Api

MCP Bridge is a lightweight, LLM-independent RESTful proxy for connecting to multiple Model Context Protocol (MCP) servers and exposing their functions through a unified REST API. It solves the problem that platforms such as edge devices, mobile devices, and web browsers cannot efficiently run MCP servers, and provides optional risk-based execution levels, including security controls such as standard execution, confirmation workflows, and Docker isolation.
2.5 points
10.2K

What is MCP Bridge?

MCP Bridge is a lightweight proxy service that connects multiple Model Context Protocol (MCP) servers and exposes their functions through a unified REST API. It allows clients on any platform to use MCP functions without directly running the MCP server process.

How to use MCP Bridge?

Interact with MCP Bridge through simple HTTP requests, and it can proxy your requests to the backend MCP servers. You can also use the accompanying MCP-Gemini Agent to interact with MCP tools in natural language.

Use cases

Suitable for scenarios where MCP functions need to be used on mobile devices, browsers, or other environments that cannot directly run MCP servers. It is also suitable for situations where multiple MCP server connections need to be centrally managed.

Main features

Multi-server support
Can connect to and manage multiple different types of MCP servers simultaneously
Unified REST API
Provides a consistent RESTful interface for all connected MCP servers
Risk level control
Supports three risk levels (low, medium, high) and provides different security execution strategies
Gemini intelligent agent
The accompanying Python client that enables natural language interaction through Google Gemini LLM
Docker isolation
Automatically uses Docker container isolation for high-risk operations
Advantages
Platform independence: Can be used on any device that can send HTTP requests
Resource efficiency: Multiple clients can share the same MCP server connection
Security controllability: Provides fine-grained security control through the risk level system
Ease of use: The accompanying Gemini Agent enables non-technical users to easily use MCP tools
Limitations
Requires an additional proxy layer, which may add a small amount of latency
High-risk levels require Docker environment support
The Gemini Agent requires a Google API key

How to use

Install MCP Bridge
Ensure that Node.js 18+ is installed, and then run npm install to install dependencies
Configure MCP servers
Edit the mcp_config.json file and add the configuration of the MCP servers you need to connect to
Start MCP Bridge
Run node mcp-bridge.js to start the proxy service
Use the API or Gemini Agent
Call the API directly through HTTP requests or use the MCP-Gemini Agent for natural language interaction

Usage examples

Browse the file system
Access and browse the file system of a remote server through MCP Bridge
Send a Slack message
Send a message to a specified channel through the Slack MCP server
Confirm high-risk operations
Execute medium-risk operations that require confirmation

Frequently Asked Questions

Which MCP servers does MCP Bridge support?
How to add a new MCP server?
How are risk levels determined?
What permissions does the Gemini Agent require?

Related resources

Official documentation of Model Context Protocol
Official documentation and specifications of the MCP protocol
GitHub repository
Source code and the latest version of MCP Bridge
List of MCP servers
List of official and community-maintained MCP servers

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/directory"],
      "riskLevel": 2
    },
    "slack": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-slack"],
      "env": {
        "SLACK_BOT_TOKEN": "your-slack-token",
        "SLACK_TEAM_ID": "your-team-id"
      },
      "riskLevel": 1
    }
  }
}
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
9.5K
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
10.1K
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
14.8K
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
6.7K
4 points
P
Paperbanana
Python
8.9K
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
8.7K
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
10.0K
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
9.8K
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
24.8K
4.5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
81.5K
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
38.1K
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
27.4K
4.3 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#
38.4K
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
69.6K
4.5 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
24.0K
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
107.3K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase