Semgrep MCP Server for Mastra AI 10 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Semgrep through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"semgrep": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Semgrep Agent",
instructions:
"You help users interact with Semgrep " +
"using 10 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Semgrep?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Semgrep MCP Server
Connect the Semgrep AppSec platform directly to your AI agent to radically accelerate code security triaging. Instead of forcing developers to jump between their IDE and the Semgrep dashboard, empower your AI to pull 'Findings', analyze the vulnerable syntax, and instantly close false positives.
Mastra's agent abstraction provides a clean separation between LLM logic and Semgrep tool infrastructure. Connect 10 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.
What you can do
- Triage Findings (Bugs) — Instruct the agent to grab the latest CI vulnerability findings and immediately push a status update to mark it as fixed, ignored, or mitigated (
update_finding_status) - Rule Management — Request the AI to look at a newly discovered bad coding pattern and command it to write and deploy a matching custom semantic rule (
create_rule) to your organizational deployment - Project & Deployment Scoping — Map out all repositories running Semgrep actions and check their overarching security health scores in milliseconds
- Comprehensive Forensics — Fetch granular SCA and SAST semantic flaw definitions, including exact snippets, CVE links, and the specific bad lines causing the trigger
The Semgrep MCP Server exposes 10 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Semgrep to Mastra AI via MCP
Follow these steps to integrate the Semgrep MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 10 tools from Semgrep via MCP
Why Use Mastra AI with the Semgrep MCP Server
Mastra AI provides unique advantages when paired with Semgrep through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Semgrep without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Semgrep tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
Semgrep + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Semgrep MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Semgrep, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Semgrep as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Semgrep on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Semgrep tools alongside other MCP servers
Semgrep MCP Tools for Mastra AI (10)
These 10 tools become available when you connect Semgrep to Mastra AI via MCP:
create_rule
Allows developers to forbid project-specific bad patterns securely and continuously across the enterprise repositories. Create a customized Semgrep security rule within the platform
delete_rule
Delete a custom Semgrep security rule from the deployment
get_finding_details
Explains the exact malicious code block, suggests semantic fixes, states whether it is blocking PRs in CI, and links to CVE data (if an SCA supply chain defect). Get atomic details for a specific Semgrep flaw
get_metrics
Typically consumed to render executive security dashboards. Get AppSec metrics and compliance stats for Semgrep
get_project
Search for a precise Semgrep project by exact repository name
list_deployments
The primary key is the deployment slug identifier. Almost all subsequent API operations targeting rules, projects, or findings will require this deployment slug to define the scope. List Semgrep organizational deployments
list_findings
Findings provide snippet details, file line numbers, severity, and rule types. Fetch global static analysis security findings for a deployment
list_projects
Projects maintain a link between developers and static security scan outputs over time. List Semgrep projects (repositories) monitored in a deployment
list_rules
The rules are structured YAML definitions that search for semantic anti-patterns in codebases (e.g., unparameterized SQL queries, hardcoded AWS keys). List Semgrep semantic rules deployed globally
update_finding_status
Valid states generally include active, fixed, false_positive, ignored, mitigated. Resolving findings through this API cleans up the developer experience when managing compliance queues. Mark a Semgrep finding state (e.g., fixed, false positive)
Example Prompts for Semgrep in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Semgrep immediately.
"List the most severe unmitigated findings currently breaking our CI/CD pipeline on the 'vinkius/cloud' repository."
"Mark vulnerability issue ID #58032 as a 'false_positive' using the update finding tool."
"Review the company's Semgrep performance metrics focusing on fix rate."
Troubleshooting Semgrep MCP Server with Mastra AI
Common issues when connecting Semgrep to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpSemgrep + Mastra AI FAQ
Common questions about integrating Semgrep MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Semgrep with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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TypeScript toolkit for building AI-powered web applications.
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Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Semgrep to Mastra AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.