⚠️ The Semgrep MCP server has been moved from a standalone repo to the main `semgrep` repository! ⚠️

This repository has been deprecated, and further updates to the Semgrep MCP server will be made via the official semgrep binary.

Semgrep MCP Server

A Model Context Protocol (MCP) server for using Semgrep to scan code for security vulnerabilities. Secure your vibe coding! 😅

Model Context Protocol (MCP) is a standardized API for LLMs, Agents, and IDEs like Cursor, VS Code, Windsurf, or anything that supports MCP, to get specialized help, get context, and harness the power of tools. Semgrep is a fast, deterministic static analysis tool that semantically understands many languages and comes with over 5,000 rules. 🛠️

Note

This beta project is under active development. We would love your feedback, bug reports, feature requests, and code. Join the #mcp community Slack channel!

Semgrep MCP Server

Getting started

Run the Python package as a CLI command using uv:

uvx semgrep-mcp # see --help for more options

Or, run as a Docker container:

docker run -i --rm ghcr.io/semgrep/mcp -t stdio

Cursor

Example mcp.json

{
  "mcpServers": {
    "semgrep": {
      "command": "uvx",
      "args": ["semgrep-mcp"],
      "env": {
        "SEMGREP_APP_TOKEN": "<token>"
      }
    }
  }
}

Add an instruction to your .cursor/rules to use automatically:

Always scan code generated using Semgrep for security vulnerabilities

ChatGPT

Go to the Connector Settings page (direct link)
Name the connection Semgrep
Set MCP Server URL to https://mcp.semgrep.ai/sse
Set Authentication to No authentication
Check the I trust this application checkbox
Click Create

See more details at the official docs.

Hosted Server

Warning

mcp.semgrep.ai is an experimental server that may break unexpectedly. It will rapidly gain new functionality.🚀

Cursor

Cmd + Shift + J to open Cursor Settings
Select MCP Tools
Click New MCP Server.

{
  "mcpServers": {
    "semgrep": {
      "type": "streamable-http",
      "url": "https://mcp.semgrep.ai/mcp"
    }
  }
}

Demo

API

Tools

Enable LLMs to perform actions, make deterministic computations, and interact with external services.

Scan Code

security_check: Scan code for security vulnerabilities
semgrep_scan: Scan code files for security vulnerabilities with a given config string
semgrep_scan_with_custom_rule: Scan code files using a custom Semgrep rule

Understand Code

get_abstract_syntax_tree: Output the Abstract Syntax Tree (AST) of code

Cloud Platform (login and Semgrep token required)

semgrep_findings: Fetch Semgrep findings from the Semgrep AppSec Platform API

Prompts

Reusable prompts to standardize common LLM interactions.

write_custom_semgrep_rule: Return a prompt to help write a Semgrep rule

Resources

Expose data and content to LLMs

semgrep://rule/schema: Specification of the Semgrep rule YAML syntax using JSON schema
semgrep://rule/{rule_id}/yaml: Full Semgrep rule in YAML format from the Semgrep registry

Usage

This Python package is published to PyPI as semgrep-mcp and can be installed and run with pip, pipx, uv, poetry, or any Python package manager.

$ pipx install semgrep-mcp
$ semgrep-mcp --help

Usage: semgrep-mcp [OPTIONS]

  Entry point for the MCP server

  Supports both stdio and sse transports. For stdio, it will read from stdin
  and write to stdout. For sse, it will start an HTTP server on port 8000.

Options:
  -v, --version                Show version and exit.
  -t, --transport [stdio|sse]  Transport protocol to use (stdio or sse)
  -h, --help                   Show this message and exit.

Standard Input/Output (stdio)

The stdio transport enables communication through standard input and output streams. This is particularly useful for local integrations and command-line tools. See the spec for more details.

Python

semgrep-mcp

By default, the Python package will run in stdio mode. Because it's using the standard input and output streams, it will look like the tool is hanging without any output, but this is expected.

Docker

This server is published to Github's Container Registry (ghcr.io/semgrep/mcp)

docker run -i --rm ghcr.io/semgrep/mcp -t stdio

By default, the Docker container is in SSE mode, so you will have to include -t stdio after the image name and run with -i to run in interactive mode.

Streamable HTTP

Streamable HTTP enables streaming responses over JSON RPC via HTTP POST requests. See the spec for more details.

By default, the server listens on 127.0.0.1:8000/mcp for client connections. To change any of this, set FASTMCP_* environment variables. The server must be running for clients to connect to it.

Python

semgrep-mcp -t streamable-http

By default, the Python package will run in stdio mode, so you will have to include -t streamable-http.

Docker

docker run -p 8000:0000 ghcr.io/semgrep/mcp

Server-sent events (SSE)

Warning

The MCP communiity considers this a legacy transport portcol and is really intended for backwards compatibility. Streamable HTTP is the recommended replacement.

SSE transport enables server-to-client streaming with Server-Send Events for client-to-server and server-to-client communication. See the spec for more details.

By default, the server listens on 127.0.0.1:8000/sse for client connections. To change any of this, set FASTMCP_* environment variables. The server must be running for clients to connect to it.

Python

semgrep-mcp -t sse

By default, the Python package will run in stdio mode, so you will have to include -t sse.

Docker

docker run -p 8000:0000 ghcr.io/semgrep/mcp -t sse

Semgrep AppSec Platform

Optionally, to connect to Semgrep AppSec Platform:

Login or sign up
Generate a token from Settings
Add the token to your environment variables:
- CLI (export SEMGREP_APP_TOKEN=<token>)
- Docker (docker run -e SEMGREP_APP_TOKEN=<token>)
- MCP config JSON

    "env": {
      "SEMGREP_APP_TOKEN": "<token>"
    }

Tip

Please reach out for support if needed. ☎️

Integrations

Cursor IDE

Add the following JSON block to your ~/.cursor/mcp.json global or .cursor/mcp.json project-specific configuration file:

{
  "mcpServers": {
    "semgrep": {
      "command": "uvx",
      "args": ["semgrep-mcp"]
    }
  }
}

See cursor docs for more info.

VS Code / Copilot

Click the install buttons at the top of this README for the quickest installation.

Manual Configuration

Add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

{
  "mcp": {
    "servers": {
      "semgrep": {
        "command": "uvx",
        "args": ["semgrep-mcp"]
      }
    }
  }
}

Optionally, you can add it to a file called .vscode/mcp.json in your workspace:

{
  "servers": {
    "semgrep": {
      "command": "uvx",
        "args": ["semgrep-mcp"]
    }
  }
}

Using Docker

{
  "mcp": {
    "servers": {
      "semgrep": {
        "command": "docker",
        "args": [
          "run",
          "-i",
          "--rm",
          "ghcr.io/semgrep/mcp",
          "-t",
          "stdio"
        ]
      }
    }
  }
}

See VS Code docs for more info.

Windsurf

Add the following JSON block to your ~/.codeium/windsurf/mcp_config.json file:

{
  "mcpServers": {
    "semgrep": {
      "command": "uvx",
      "args": ["semgrep-mcp"]
    }
  }
}

See Windsurf docs for more info.

Claude Desktop

Here is a short video showing Claude Desktop using this server to write a custom rule.

Add the following JSON block to your claude_desktop_config.json file:

{
  "mcpServers": {
    "semgrep": {
      "command": "uvx",
      "args": ["semgrep-mcp"]
    }
  }
}

See Anthropic docs for more info.

Claude Code

claude mcp add semgrep uvx semgrep-mcp

See Claude Code docs for more info.

OpenAI

See the offical docs:

Agents SDK

async with MCPServerStdio(
    params={
        "command": "uvx",
        "args": ["semgrep-mcp"],
    }
) as server:
    tools = await server.list_tools()

See OpenAI Agents SDK docs for more info.

Custom clients

Example Python SSE client

See a full example in examples/sse_client.py

from mcp.client.session import ClientSession
from mcp.client.sse import sse_client


async def main():
    async with sse_client("http://localhost:8000/sse") as (read_stream, write_stream):
        async with ClientSession(read_stream, write_stream) as session:
            await session.initialize()
            results = await session.call_tool(
                "semgrep_scan",
                {
                    "code_files": [
                        {
                            "path": "hello_world.py",
                            "content": "def hello(): print('Hello, World!')",
                        }
                    ]
                },
            )
            print(results)

Tip

Some client libraries want the URL: http://localhost:8000/sse and others only want the HOST: localhost:8000. Try out the URL in a web browser to confirm the server is running, and there are no network issues.

See official SDK docs for more info.

Contributing, community, and running from source

Note

We love your feedback, bug reports, feature requests, and code. Join the #mcp community Slack channel!

See CONTRIBUTING.md for more info and details on how to run from the MCP server from source code.

Similar tools 🔍

semgrep-vscode - Official VS Code extension
semgrep-intellij - IntelliJ plugin

Community projects 🌟

semgrep-rules - The official collection of Semgrep rules
mcp-server-semgrep - Original inspiration written by Szowesgad and stefanskiasan

MCP server registries

Glama

MCP.so

Made with ❤️ by the Semgrep Team

⚠️ The Semgrep MCP server has been moved from a standalone repo to the main semgrep repository! ⚠️

Semgrep MCP Server

Contents

Getting started

Cursor

ChatGPT

Hosted Server

Cursor

Demo

API

Tools

Scan Code

Understand Code

Cloud Platform (login and Semgrep token required)

Meta

Prompts

Resources

Usage

Standard Input/Output (stdio)

Python

Docker

Streamable HTTP

Python

Docker

Server-sent events (SSE)

Python

Docker

Semgrep AppSec Platform

Integrations

Cursor IDE

VS Code / Copilot

Manual Configuration

Using Docker

Windsurf

Claude Desktop

Claude Code

OpenAI

Agents SDK

Custom clients

Example Python SSE client

Contributing, community, and running from source

Similar tools 🔍

Community projects 🌟

MCP server registries

⚠️ The Semgrep MCP server has been moved from a standalone repo to the main `semgrep` repository! ⚠️

Features

Rate this server

Features

Rate this server